KoichiYasuoka
commited on
Commit
•
f59d332
1
Parent(s):
c049273
initial release
Browse files- README.md +33 -0
- config.json +1676 -0
- maker.py +108 -0
- merges.txt +0 -0
- pytorch_model-00001-of-00002.bin +3 -0
- pytorch_model-00002-of-00002.bin +3 -0
- pytorch_model.bin.index.json +347 -0
- special_tokens_map.json +42 -0
- tokenizer_config.json +54 -0
- ud.py +121 -0
- vocab.json +0 -0
README.md
ADDED
@@ -0,0 +1,33 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
language:
|
3 |
+
- lzh
|
4 |
+
tags:
|
5 |
+
- classical chinese
|
6 |
+
- literary chinese
|
7 |
+
- ancient chinese
|
8 |
+
- token-classification
|
9 |
+
- pos
|
10 |
+
- dependency-parsing
|
11 |
+
base_model: KoichiYasuoka/Xunzi-Qwen2-1.5B-upos
|
12 |
+
datasets:
|
13 |
+
- universal_dependencies
|
14 |
+
license: apache-2.0
|
15 |
+
pipeline_tag: token-classification
|
16 |
+
widget:
|
17 |
+
- text: 子曰學而時習之不亦説乎有朋自遠方來不亦樂乎人不知而不慍不亦君子乎
|
18 |
+
---
|
19 |
+
|
20 |
+
# Xunzi-Qwen2-1.5B-ud-causal
|
21 |
+
|
22 |
+
## Model Description
|
23 |
+
|
24 |
+
This is a LLaMA model pretrained for POS-tagging and dependency-parsing, derived from [Xunzi-Qwen2-1.5B-upos](https://huggingface.co/KoichiYasuoka/Xunzi-Qwen2-1.5B-upos) and [UD_Classical_Chinese-Kyoto](https://github.com/UniversalDependencies/UD_Classical_Chinese-Kyoto).
|
25 |
+
|
26 |
+
## How to Use
|
27 |
+
|
28 |
+
```
|
29 |
+
from transformers import pipeline
|
30 |
+
nlp=pipeline("universal-dependencies","KoichiYasuoka/Xunzi-Qwen2-1.5B-ud-causal",trust_remote_code=True)
|
31 |
+
print(nlp("不入虎穴不得虎子"))
|
32 |
+
```
|
33 |
+
|
config.json
ADDED
@@ -0,0 +1,1676 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"architectures": [
|
3 |
+
"Qwen2ForTokenClassification"
|
4 |
+
],
|
5 |
+
"attention_dropout": 0.0,
|
6 |
+
"bos_token_id": 151643,
|
7 |
+
"custom_pipelines": {
|
8 |
+
"upos": {
|
9 |
+
"impl": "ud.BellmanFordTokenClassificationPipeline",
|
10 |
+
"pt": "AutoModelForTokenClassification"
|
11 |
+
},
|
12 |
+
"universal-dependencies": {
|
13 |
+
"impl": "ud.UniversalDependenciesCausalPipeline",
|
14 |
+
"pt": "AutoModelForTokenClassification"
|
15 |
+
}
|
16 |
+
},
|
17 |
+
"eos_token_id": 151643,
|
18 |
+
"hidden_act": "silu",
|
19 |
+
"hidden_size": 1536,
|
20 |
+
"id2label": {
|
21 |
+
"0": "ADP",
|
22 |
+
"1": "ADP|Degree=Equ",
|
23 |
+
"2": "ADP|Degree=Equ|l-cc",
|
24 |
+
"3": "ADP|l-acl",
|
25 |
+
"4": "ADP|l-advcl",
|
26 |
+
"5": "ADP|l-amod",
|
27 |
+
"6": "ADP|l-case",
|
28 |
+
"7": "ADP|l-cc",
|
29 |
+
"8": "ADP|l-mark",
|
30 |
+
"9": "ADP|l-nsubj",
|
31 |
+
"10": "ADP|l-obl",
|
32 |
+
"11": "ADP|r-case",
|
33 |
+
"12": "ADP|r-conj",
|
34 |
+
"13": "ADP|r-fixed",
|
35 |
+
"14": "ADP|r-mark",
|
36 |
+
"15": "ADP|r-obj",
|
37 |
+
"16": "ADP|root",
|
38 |
+
"17": "ADV",
|
39 |
+
"18": "ADV|AdvType=Cau",
|
40 |
+
"19": "ADV|AdvType=Cau|l-advmod",
|
41 |
+
"20": "ADV|AdvType=Cau|l-amod",
|
42 |
+
"21": "ADV|AdvType=Cau|l-nsubj",
|
43 |
+
"22": "ADV|AdvType=Cau|l-obj",
|
44 |
+
"23": "ADV|AdvType=Deg|Degree=Cmp",
|
45 |
+
"24": "ADV|AdvType=Deg|Degree=Cmp|l-advmod",
|
46 |
+
"25": "ADV|AdvType=Deg|Degree=Cmp|l-amod",
|
47 |
+
"26": "ADV|AdvType=Deg|Degree=Cmp|r-conj",
|
48 |
+
"27": "ADV|AdvType=Deg|Degree=Cmp|r-obj",
|
49 |
+
"28": "ADV|AdvType=Deg|Degree=Pos",
|
50 |
+
"29": "ADV|AdvType=Deg|Degree=Pos|l-advmod",
|
51 |
+
"30": "ADV|AdvType=Deg|Degree=Pos|l-amod",
|
52 |
+
"31": "ADV|AdvType=Deg|Degree=Pos|r-ccomp",
|
53 |
+
"32": "ADV|AdvType=Deg|Degree=Pos|r-conj",
|
54 |
+
"33": "ADV|AdvType=Deg|Degree=Pos|r-flat:vv",
|
55 |
+
"34": "ADV|AdvType=Deg|Degree=Pos|r-parataxis",
|
56 |
+
"35": "ADV|AdvType=Deg|Degree=Pos|root",
|
57 |
+
"36": "ADV|AdvType=Deg|Degree=Sup",
|
58 |
+
"37": "ADV|AdvType=Deg|Degree=Sup|l-advmod",
|
59 |
+
"38": "ADV|AdvType=Deg|Degree=Sup|l-amod",
|
60 |
+
"39": "ADV|AdvType=Deg|Degree=Sup|l-nsubj",
|
61 |
+
"40": "ADV|AdvType=Deg|Degree=Sup|r-conj",
|
62 |
+
"41": "ADV|AdvType=Deg|Degree=Sup|r-parataxis",
|
63 |
+
"42": "ADV|AdvType=Deg|Degree=Sup|root",
|
64 |
+
"43": "ADV|AdvType=Tim",
|
65 |
+
"44": "ADV|AdvType=Tim|Aspect=Perf",
|
66 |
+
"45": "ADV|AdvType=Tim|Aspect=Perf|l-advmod",
|
67 |
+
"46": "ADV|AdvType=Tim|Aspect=Perf|l-amod",
|
68 |
+
"47": "ADV|AdvType=Tim|Aspect=Perf|l-obl:lmod",
|
69 |
+
"48": "ADV|AdvType=Tim|Aspect=Perf|r-parataxis",
|
70 |
+
"49": "ADV|AdvType=Tim|Aspect=Perf|root",
|
71 |
+
"50": "ADV|AdvType=Tim|Tense=Fut",
|
72 |
+
"51": "ADV|AdvType=Tim|Tense=Fut|l-advmod",
|
73 |
+
"52": "ADV|AdvType=Tim|Tense=Fut|l-amod",
|
74 |
+
"53": "ADV|AdvType=Tim|Tense=Fut|l-nsubj",
|
75 |
+
"54": "ADV|AdvType=Tim|Tense=Fut|l-nsubj:outer",
|
76 |
+
"55": "ADV|AdvType=Tim|Tense=Fut|root",
|
77 |
+
"56": "ADV|AdvType=Tim|Tense=Past",
|
78 |
+
"57": "ADV|AdvType=Tim|Tense=Past|l-advmod",
|
79 |
+
"58": "ADV|AdvType=Tim|Tense=Past|l-amod",
|
80 |
+
"59": "ADV|AdvType=Tim|Tense=Pres",
|
81 |
+
"60": "ADV|AdvType=Tim|Tense=Pres|l-advmod",
|
82 |
+
"61": "ADV|AdvType=Tim|Tense=Pres|l-amod",
|
83 |
+
"62": "ADV|AdvType=Tim|Tense=Pres|root",
|
84 |
+
"63": "ADV|AdvType=Tim|l-advcl",
|
85 |
+
"64": "ADV|AdvType=Tim|l-advmod",
|
86 |
+
"65": "ADV|AdvType=Tim|l-amod",
|
87 |
+
"66": "ADV|AdvType=Tim|l-nsubj",
|
88 |
+
"67": "ADV|AdvType=Tim|r-advmod",
|
89 |
+
"68": "ADV|AdvType=Tim|r-ccomp",
|
90 |
+
"69": "ADV|AdvType=Tim|r-compound:redup",
|
91 |
+
"70": "ADV|AdvType=Tim|r-conj",
|
92 |
+
"71": "ADV|AdvType=Tim|r-flat:vv",
|
93 |
+
"72": "ADV|AdvType=Tim|r-parataxis",
|
94 |
+
"73": "ADV|AdvType=Tim|root",
|
95 |
+
"74": "ADV|Degree=Equ|VerbForm=Conv",
|
96 |
+
"75": "ADV|Degree=Equ|VerbForm=Conv|l-advmod",
|
97 |
+
"76": "ADV|Degree=Pos|VerbForm=Conv",
|
98 |
+
"77": "ADV|Degree=Pos|VerbForm=Conv|l-advmod",
|
99 |
+
"78": "ADV|Degree=Pos|VerbForm=Conv|r-advmod",
|
100 |
+
"79": "ADV|Polarity=Neg",
|
101 |
+
"80": "ADV|Polarity=Neg|VerbForm=Conv",
|
102 |
+
"81": "ADV|Polarity=Neg|VerbForm=Conv|l-advmod",
|
103 |
+
"82": "ADV|Polarity=Neg|l-advmod",
|
104 |
+
"83": "ADV|Polarity=Neg|l-amod",
|
105 |
+
"84": "ADV|Polarity=Neg|l-nsubj",
|
106 |
+
"85": "ADV|Polarity=Neg|l-parataxis",
|
107 |
+
"86": "ADV|Polarity=Neg|r-advmod",
|
108 |
+
"87": "ADV|Polarity=Neg|r-conj",
|
109 |
+
"88": "ADV|Polarity=Neg|r-obj",
|
110 |
+
"89": "ADV|Polarity=Neg|r-parataxis",
|
111 |
+
"90": "ADV|Polarity=Neg|root",
|
112 |
+
"91": "ADV|VerbForm=Conv",
|
113 |
+
"92": "ADV|VerbForm=Conv|l-advmod",
|
114 |
+
"93": "ADV|VerbForm=Conv|r-advmod",
|
115 |
+
"94": "ADV|l-acl",
|
116 |
+
"95": "ADV|l-advcl",
|
117 |
+
"96": "ADV|l-advmod",
|
118 |
+
"97": "ADV|l-amod",
|
119 |
+
"98": "ADV|l-cc",
|
120 |
+
"99": "ADV|l-nsubj",
|
121 |
+
"100": "ADV|r-advmod",
|
122 |
+
"101": "ADV|r-ccomp",
|
123 |
+
"102": "ADV|r-conj",
|
124 |
+
"103": "ADV|r-flat:vv",
|
125 |
+
"104": "ADV|r-obj",
|
126 |
+
"105": "ADV|root",
|
127 |
+
"106": "AUX|Mood=Des",
|
128 |
+
"107": "AUX|Mood=Des|l-aux",
|
129 |
+
"108": "AUX|Mood=Des|l-csubj",
|
130 |
+
"109": "AUX|Mood=Des|l-parataxis",
|
131 |
+
"110": "AUX|Mood=Des|r-ccomp",
|
132 |
+
"111": "AUX|Mood=Des|r-conj",
|
133 |
+
"112": "AUX|Mood=Des|r-flat:vv",
|
134 |
+
"113": "AUX|Mood=Des|root",
|
135 |
+
"114": "AUX|Mood=Nec",
|
136 |
+
"115": "AUX|Mood=Nec|l-acl",
|
137 |
+
"116": "AUX|Mood=Nec|l-amod",
|
138 |
+
"117": "AUX|Mood=Nec|l-aux",
|
139 |
+
"118": "AUX|Mood=Nec|r-aux",
|
140 |
+
"119": "AUX|Mood=Nec|root",
|
141 |
+
"120": "AUX|Mood=Pot",
|
142 |
+
"121": "AUX|Mood=Pot|l-acl",
|
143 |
+
"122": "AUX|Mood=Pot|l-advcl",
|
144 |
+
"123": "AUX|Mood=Pot|l-amod",
|
145 |
+
"124": "AUX|Mood=Pot|l-aux",
|
146 |
+
"125": "AUX|Mood=Pot|l-csubj",
|
147 |
+
"126": "AUX|Mood=Pot|l-nsubj",
|
148 |
+
"127": "AUX|Mood=Pot|r-ccomp",
|
149 |
+
"128": "AUX|Mood=Pot|r-conj",
|
150 |
+
"129": "AUX|Mood=Pot|r-obj",
|
151 |
+
"130": "AUX|Mood=Pot|r-parataxis",
|
152 |
+
"131": "AUX|Mood=Pot|r-xcomp",
|
153 |
+
"132": "AUX|Mood=Pot|root",
|
154 |
+
"133": "AUX|VerbType=Cop",
|
155 |
+
"134": "AUX|VerbType=Cop|l-cop",
|
156 |
+
"135": "AUX|Voice=Pass",
|
157 |
+
"136": "AUX|Voice=Pass|l-aux",
|
158 |
+
"137": "AUX|Voice=Pass|r-conj",
|
159 |
+
"138": "AUX|Voice=Pass|root",
|
160 |
+
"139": "B-ADP",
|
161 |
+
"140": "B-ADP|Degree=Equ",
|
162 |
+
"141": "B-ADV",
|
163 |
+
"142": "B-ADV|AdvType=Cau",
|
164 |
+
"143": "B-ADV|AdvType=Deg|Degree=Cmp",
|
165 |
+
"144": "B-ADV|AdvType=Deg|Degree=Pos",
|
166 |
+
"145": "B-ADV|AdvType=Deg|Degree=Sup",
|
167 |
+
"146": "B-ADV|AdvType=Tim",
|
168 |
+
"147": "B-ADV|AdvType=Tim|Aspect=Perf",
|
169 |
+
"148": "B-ADV|AdvType=Tim|Tense=Fut",
|
170 |
+
"149": "B-ADV|AdvType=Tim|Tense=Past",
|
171 |
+
"150": "B-ADV|AdvType=Tim|Tense=Pres",
|
172 |
+
"151": "B-ADV|Degree=Equ|VerbForm=Conv",
|
173 |
+
"152": "B-ADV|Degree=Pos|VerbForm=Conv",
|
174 |
+
"153": "B-ADV|Polarity=Neg",
|
175 |
+
"154": "B-ADV|Polarity=Neg|VerbForm=Conv",
|
176 |
+
"155": "B-ADV|VerbForm=Conv",
|
177 |
+
"156": "B-AUX|Mood=Des",
|
178 |
+
"157": "B-AUX|Mood=Nec",
|
179 |
+
"158": "B-AUX|Mood=Pot",
|
180 |
+
"159": "B-AUX|VerbType=Cop",
|
181 |
+
"160": "B-AUX|Voice=Pass",
|
182 |
+
"161": "B-CCONJ",
|
183 |
+
"162": "B-INTJ",
|
184 |
+
"163": "B-NOUN",
|
185 |
+
"164": "B-NOUN|Case=Loc",
|
186 |
+
"165": "B-NOUN|Case=Tem",
|
187 |
+
"166": "B-NOUN|Degree=Pos",
|
188 |
+
"167": "B-NOUN|NounType=Clf",
|
189 |
+
"168": "B-NUM",
|
190 |
+
"169": "B-NUM|NumType=Ord",
|
191 |
+
"170": "B-PART",
|
192 |
+
"171": "B-PRON|Person=1|PronType=Prs",
|
193 |
+
"172": "B-PRON|Person=2|PronType=Prs",
|
194 |
+
"173": "B-PRON|Person=3|PronType=Prs",
|
195 |
+
"174": "B-PRON|PronType=Dem",
|
196 |
+
"175": "B-PRON|PronType=Int",
|
197 |
+
"176": "B-PRON|PronType=Prs",
|
198 |
+
"177": "B-PRON|PronType=Prs|Reflex=Yes",
|
199 |
+
"178": "B-PROPN",
|
200 |
+
"179": "B-PROPN|Case=Loc|NameType=Geo",
|
201 |
+
"180": "B-PROPN|Case=Loc|NameType=Nat",
|
202 |
+
"181": "B-PROPN|NameType=Giv",
|
203 |
+
"182": "B-PROPN|NameType=Prs",
|
204 |
+
"183": "B-PROPN|NameType=Sur",
|
205 |
+
"184": "B-PUNCT",
|
206 |
+
"185": "B-SCONJ",
|
207 |
+
"186": "B-SYM",
|
208 |
+
"187": "B-VERB",
|
209 |
+
"188": "B-VERB|Degree=Equ",
|
210 |
+
"189": "B-VERB|Degree=Equ|VerbForm=Part",
|
211 |
+
"190": "B-VERB|Degree=Pos",
|
212 |
+
"191": "B-VERB|Degree=Pos|VerbForm=Part",
|
213 |
+
"192": "B-VERB|Polarity=Neg",
|
214 |
+
"193": "B-VERB|Polarity=Neg|VerbForm=Part",
|
215 |
+
"194": "B-VERB|VerbForm=Part",
|
216 |
+
"195": "CCONJ",
|
217 |
+
"196": "CCONJ|l-advmod",
|
218 |
+
"197": "CCONJ|l-amod",
|
219 |
+
"198": "CCONJ|l-cc",
|
220 |
+
"199": "CCONJ|l-obj",
|
221 |
+
"200": "CCONJ|r-fixed",
|
222 |
+
"201": "CCONJ|r-orphan",
|
223 |
+
"202": "I-ADP",
|
224 |
+
"203": "I-ADP|Degree=Equ",
|
225 |
+
"204": "I-ADV",
|
226 |
+
"205": "I-ADV|AdvType=Cau",
|
227 |
+
"206": "I-ADV|AdvType=Deg|Degree=Cmp",
|
228 |
+
"207": "I-ADV|AdvType=Deg|Degree=Pos",
|
229 |
+
"208": "I-ADV|AdvType=Deg|Degree=Sup",
|
230 |
+
"209": "I-ADV|AdvType=Tim",
|
231 |
+
"210": "I-ADV|AdvType=Tim|Aspect=Perf",
|
232 |
+
"211": "I-ADV|AdvType=Tim|Tense=Fut",
|
233 |
+
"212": "I-ADV|AdvType=Tim|Tense=Past",
|
234 |
+
"213": "I-ADV|AdvType=Tim|Tense=Pres",
|
235 |
+
"214": "I-ADV|Degree=Equ|VerbForm=Conv",
|
236 |
+
"215": "I-ADV|Degree=Pos|VerbForm=Conv",
|
237 |
+
"216": "I-ADV|Polarity=Neg",
|
238 |
+
"217": "I-ADV|Polarity=Neg|VerbForm=Conv",
|
239 |
+
"218": "I-ADV|VerbForm=Conv",
|
240 |
+
"219": "I-AUX|Mood=Des",
|
241 |
+
"220": "I-AUX|Mood=Nec",
|
242 |
+
"221": "I-AUX|Mood=Pot",
|
243 |
+
"222": "I-AUX|VerbType=Cop",
|
244 |
+
"223": "I-AUX|Voice=Pass",
|
245 |
+
"224": "I-CCONJ",
|
246 |
+
"225": "I-INTJ",
|
247 |
+
"226": "I-NOUN",
|
248 |
+
"227": "I-NOUN|Case=Loc",
|
249 |
+
"228": "I-NOUN|Case=Tem",
|
250 |
+
"229": "I-NOUN|Degree=Pos",
|
251 |
+
"230": "I-NOUN|NounType=Clf",
|
252 |
+
"231": "I-NUM",
|
253 |
+
"232": "I-NUM|NumType=Ord",
|
254 |
+
"233": "I-PART",
|
255 |
+
"234": "I-PRON|Person=1|PronType=Prs",
|
256 |
+
"235": "I-PRON|Person=2|PronType=Prs",
|
257 |
+
"236": "I-PRON|Person=3|PronType=Prs",
|
258 |
+
"237": "I-PRON|PronType=Dem",
|
259 |
+
"238": "I-PRON|PronType=Int",
|
260 |
+
"239": "I-PRON|PronType=Prs",
|
261 |
+
"240": "I-PRON|PronType=Prs|Reflex=Yes",
|
262 |
+
"241": "I-PROPN",
|
263 |
+
"242": "I-PROPN|Case=Loc|NameType=Geo",
|
264 |
+
"243": "I-PROPN|Case=Loc|NameType=Nat",
|
265 |
+
"244": "I-PROPN|NameType=Giv",
|
266 |
+
"245": "I-PROPN|NameType=Prs",
|
267 |
+
"246": "I-PROPN|NameType=Sur",
|
268 |
+
"247": "I-PUNCT",
|
269 |
+
"248": "I-SCONJ",
|
270 |
+
"249": "I-SYM",
|
271 |
+
"250": "I-VERB",
|
272 |
+
"251": "I-VERB|Degree=Equ",
|
273 |
+
"252": "I-VERB|Degree=Equ|VerbForm=Part",
|
274 |
+
"253": "I-VERB|Degree=Pos",
|
275 |
+
"254": "I-VERB|Degree=Pos|VerbForm=Part",
|
276 |
+
"255": "I-VERB|Polarity=Neg",
|
277 |
+
"256": "I-VERB|Polarity=Neg|VerbForm=Part",
|
278 |
+
"257": "I-VERB|VerbForm=Part",
|
279 |
+
"258": "INTJ",
|
280 |
+
"259": "INTJ|l-advcl",
|
281 |
+
"260": "INTJ|l-csubj",
|
282 |
+
"261": "INTJ|l-discourse",
|
283 |
+
"262": "INTJ|l-discourse:sp",
|
284 |
+
"263": "INTJ|l-dislocated",
|
285 |
+
"264": "INTJ|l-nsubj",
|
286 |
+
"265": "INTJ|l-vocative",
|
287 |
+
"266": "INTJ|r-compound:redup",
|
288 |
+
"267": "INTJ|r-conj",
|
289 |
+
"268": "INTJ|r-discourse:sp",
|
290 |
+
"269": "INTJ|r-dislocated",
|
291 |
+
"270": "INTJ|r-fixed",
|
292 |
+
"271": "INTJ|r-obj",
|
293 |
+
"272": "INTJ|r-parataxis",
|
294 |
+
"273": "INTJ|root",
|
295 |
+
"274": "NOUN",
|
296 |
+
"275": "NOUN|Case=Loc",
|
297 |
+
"276": "NOUN|Case=Loc|l-acl",
|
298 |
+
"277": "NOUN|Case=Loc|l-advcl",
|
299 |
+
"278": "NOUN|Case=Loc|l-amod",
|
300 |
+
"279": "NOUN|Case=Loc|l-clf",
|
301 |
+
"280": "NOUN|Case=Loc|l-compound",
|
302 |
+
"281": "NOUN|Case=Loc|l-csubj",
|
303 |
+
"282": "NOUN|Case=Loc|l-dislocated",
|
304 |
+
"283": "NOUN|Case=Loc|l-nmod",
|
305 |
+
"284": "NOUN|Case=Loc|l-nsubj",
|
306 |
+
"285": "NOUN|Case=Loc|l-nsubj:outer",
|
307 |
+
"286": "NOUN|Case=Loc|l-obj",
|
308 |
+
"287": "NOUN|Case=Loc|l-obl",
|
309 |
+
"288": "NOUN|Case=Loc|l-obl:lmod",
|
310 |
+
"289": "NOUN|Case=Loc|l-obl:tmod",
|
311 |
+
"290": "NOUN|Case=Loc|l-parataxis",
|
312 |
+
"291": "NOUN|Case=Loc|r-ccomp",
|
313 |
+
"292": "NOUN|Case=Loc|r-clf",
|
314 |
+
"293": "NOUN|Case=Loc|r-compound:redup",
|
315 |
+
"294": "NOUN|Case=Loc|r-conj",
|
316 |
+
"295": "NOUN|Case=Loc|r-dislocated",
|
317 |
+
"296": "NOUN|Case=Loc|r-flat",
|
318 |
+
"297": "NOUN|Case=Loc|r-iobj",
|
319 |
+
"298": "NOUN|Case=Loc|r-list",
|
320 |
+
"299": "NOUN|Case=Loc|r-nmod",
|
321 |
+
"300": "NOUN|Case=Loc|r-nsubj",
|
322 |
+
"301": "NOUN|Case=Loc|r-obj",
|
323 |
+
"302": "NOUN|Case=Loc|r-obl",
|
324 |
+
"303": "NOUN|Case=Loc|r-obl:lmod",
|
325 |
+
"304": "NOUN|Case=Loc|r-parataxis",
|
326 |
+
"305": "NOUN|Case=Loc|r-xcomp",
|
327 |
+
"306": "NOUN|Case=Loc|root",
|
328 |
+
"307": "NOUN|Case=Tem",
|
329 |
+
"308": "NOUN|Case=Tem|l-acl",
|
330 |
+
"309": "NOUN|Case=Tem|l-advcl",
|
331 |
+
"310": "NOUN|Case=Tem|l-amod",
|
332 |
+
"311": "NOUN|Case=Tem|l-compound",
|
333 |
+
"312": "NOUN|Case=Tem|l-csubj",
|
334 |
+
"313": "NOUN|Case=Tem|l-nmod",
|
335 |
+
"314": "NOUN|Case=Tem|l-nsubj",
|
336 |
+
"315": "NOUN|Case=Tem|l-nsubj:outer",
|
337 |
+
"316": "NOUN|Case=Tem|l-obj",
|
338 |
+
"317": "NOUN|Case=Tem|l-obl:tmod",
|
339 |
+
"318": "NOUN|Case=Tem|r-amod",
|
340 |
+
"319": "NOUN|Case=Tem|r-ccomp",
|
341 |
+
"320": "NOUN|Case=Tem|r-clf",
|
342 |
+
"321": "NOUN|Case=Tem|r-compound:redup",
|
343 |
+
"322": "NOUN|Case=Tem|r-conj",
|
344 |
+
"323": "NOUN|Case=Tem|r-flat",
|
345 |
+
"324": "NOUN|Case=Tem|r-iobj",
|
346 |
+
"325": "NOUN|Case=Tem|r-list",
|
347 |
+
"326": "NOUN|Case=Tem|r-nsubj",
|
348 |
+
"327": "NOUN|Case=Tem|r-obj",
|
349 |
+
"328": "NOUN|Case=Tem|r-obl:tmod",
|
350 |
+
"329": "NOUN|Case=Tem|r-parataxis",
|
351 |
+
"330": "NOUN|Case=Tem|r-xcomp",
|
352 |
+
"331": "NOUN|Case=Tem|root",
|
353 |
+
"332": "NOUN|Degree=Pos",
|
354 |
+
"333": "NOUN|Degree=Pos|root",
|
355 |
+
"334": "NOUN|NounType=Clf",
|
356 |
+
"335": "NOUN|NounType=Clf|l-clf",
|
357 |
+
"336": "NOUN|NounType=Clf|l-nmod",
|
358 |
+
"337": "NOUN|NounType=Clf|l-nsubj",
|
359 |
+
"338": "NOUN|NounType=Clf|l-obl",
|
360 |
+
"339": "NOUN|NounType=Clf|r-ccomp",
|
361 |
+
"340": "NOUN|NounType=Clf|r-clf",
|
362 |
+
"341": "NOUN|NounType=Clf|r-compound:redup",
|
363 |
+
"342": "NOUN|NounType=Clf|r-conj",
|
364 |
+
"343": "NOUN|NounType=Clf|r-flat",
|
365 |
+
"344": "NOUN|NounType=Clf|r-obj",
|
366 |
+
"345": "NOUN|NounType=Clf|r-parataxis",
|
367 |
+
"346": "NOUN|NounType=Clf|root",
|
368 |
+
"347": "NOUN|l-acl",
|
369 |
+
"348": "NOUN|l-advcl",
|
370 |
+
"349": "NOUN|l-amod",
|
371 |
+
"350": "NOUN|l-ccomp",
|
372 |
+
"351": "NOUN|l-clf",
|
373 |
+
"352": "NOUN|l-compound",
|
374 |
+
"353": "NOUN|l-csubj",
|
375 |
+
"354": "NOUN|l-csubj:outer",
|
376 |
+
"355": "NOUN|l-dislocated",
|
377 |
+
"356": "NOUN|l-iobj",
|
378 |
+
"357": "NOUN|l-list",
|
379 |
+
"358": "NOUN|l-nmod",
|
380 |
+
"359": "NOUN|l-nsubj",
|
381 |
+
"360": "NOUN|l-nsubj:outer",
|
382 |
+
"361": "NOUN|l-nsubj:pass",
|
383 |
+
"362": "NOUN|l-obj",
|
384 |
+
"363": "NOUN|l-obl",
|
385 |
+
"364": "NOUN|l-obl:lmod",
|
386 |
+
"365": "NOUN|l-obl:tmod",
|
387 |
+
"366": "NOUN|l-vocative",
|
388 |
+
"367": "NOUN|r-acl",
|
389 |
+
"368": "NOUN|r-advcl",
|
390 |
+
"369": "NOUN|r-amod",
|
391 |
+
"370": "NOUN|r-ccomp",
|
392 |
+
"371": "NOUN|r-clf",
|
393 |
+
"372": "NOUN|r-compound:redup",
|
394 |
+
"373": "NOUN|r-conj",
|
395 |
+
"374": "NOUN|r-csubj",
|
396 |
+
"375": "NOUN|r-dislocated",
|
397 |
+
"376": "NOUN|r-flat",
|
398 |
+
"377": "NOUN|r-flat:foreign",
|
399 |
+
"378": "NOUN|r-iobj",
|
400 |
+
"379": "NOUN|r-list",
|
401 |
+
"380": "NOUN|r-nmod",
|
402 |
+
"381": "NOUN|r-nsubj",
|
403 |
+
"382": "NOUN|r-obj",
|
404 |
+
"383": "NOUN|r-obl",
|
405 |
+
"384": "NOUN|r-obl:lmod",
|
406 |
+
"385": "NOUN|r-parataxis",
|
407 |
+
"386": "NOUN|r-vocative",
|
408 |
+
"387": "NOUN|r-xcomp",
|
409 |
+
"388": "NOUN|root",
|
410 |
+
"389": "NUM",
|
411 |
+
"390": "NUM|NumType=Ord",
|
412 |
+
"391": "NUM|NumType=Ord|l-nsubj",
|
413 |
+
"392": "NUM|NumType=Ord|l-nummod",
|
414 |
+
"393": "NUM|NumType=Ord|l-obl",
|
415 |
+
"394": "NUM|NumType=Ord|l-obl:lmod",
|
416 |
+
"395": "NUM|NumType=Ord|l-obl:tmod",
|
417 |
+
"396": "NUM|NumType=Ord|r-conj",
|
418 |
+
"397": "NUM|NumType=Ord|r-flat",
|
419 |
+
"398": "NUM|NumType=Ord|r-obj",
|
420 |
+
"399": "NUM|NumType=Ord|root",
|
421 |
+
"400": "NUM|l-acl",
|
422 |
+
"401": "NUM|l-advcl",
|
423 |
+
"402": "NUM|l-compound",
|
424 |
+
"403": "NUM|l-csubj",
|
425 |
+
"404": "NUM|l-dislocated",
|
426 |
+
"405": "NUM|l-nsubj",
|
427 |
+
"406": "NUM|l-nsubj:outer",
|
428 |
+
"407": "NUM|l-nummod",
|
429 |
+
"408": "NUM|l-obj",
|
430 |
+
"409": "NUM|l-obl",
|
431 |
+
"410": "NUM|l-obl:lmod",
|
432 |
+
"411": "NUM|l-obl:tmod",
|
433 |
+
"412": "NUM|r-ccomp",
|
434 |
+
"413": "NUM|r-clf",
|
435 |
+
"414": "NUM|r-compound",
|
436 |
+
"415": "NUM|r-compound:redup",
|
437 |
+
"416": "NUM|r-conj",
|
438 |
+
"417": "NUM|r-flat",
|
439 |
+
"418": "NUM|r-iobj",
|
440 |
+
"419": "NUM|r-list",
|
441 |
+
"420": "NUM|r-nummod",
|
442 |
+
"421": "NUM|r-obj",
|
443 |
+
"422": "NUM|r-obl",
|
444 |
+
"423": "NUM|r-obl:tmod",
|
445 |
+
"424": "NUM|r-parataxis",
|
446 |
+
"425": "NUM|r-xcomp",
|
447 |
+
"426": "NUM|root",
|
448 |
+
"427": "PART",
|
449 |
+
"428": "PART|l-acl",
|
450 |
+
"429": "PART|l-advcl",
|
451 |
+
"430": "PART|l-advmod",
|
452 |
+
"431": "PART|l-amod",
|
453 |
+
"432": "PART|l-case",
|
454 |
+
"433": "PART|l-cc",
|
455 |
+
"434": "PART|l-csubj",
|
456 |
+
"435": "PART|l-csubj:outer",
|
457 |
+
"436": "PART|l-discourse",
|
458 |
+
"437": "PART|l-discourse:sp",
|
459 |
+
"438": "PART|l-dislocated",
|
460 |
+
"439": "PART|l-mark",
|
461 |
+
"440": "PART|l-nmod",
|
462 |
+
"441": "PART|l-nsubj",
|
463 |
+
"442": "PART|l-nsubj:outer",
|
464 |
+
"443": "PART|l-nsubj:pass",
|
465 |
+
"444": "PART|l-obj",
|
466 |
+
"445": "PART|l-obl",
|
467 |
+
"446": "PART|l-obl:lmod",
|
468 |
+
"447": "PART|r-advmod",
|
469 |
+
"448": "PART|r-case",
|
470 |
+
"449": "PART|r-ccomp",
|
471 |
+
"450": "PART|r-clf",
|
472 |
+
"451": "PART|r-conj",
|
473 |
+
"452": "PART|r-discourse",
|
474 |
+
"453": "PART|r-discourse:sp",
|
475 |
+
"454": "PART|r-dislocated",
|
476 |
+
"455": "PART|r-fixed",
|
477 |
+
"456": "PART|r-flat",
|
478 |
+
"457": "PART|r-iobj",
|
479 |
+
"458": "PART|r-list",
|
480 |
+
"459": "PART|r-mark",
|
481 |
+
"460": "PART|r-nsubj",
|
482 |
+
"461": "PART|r-obj",
|
483 |
+
"462": "PART|r-obl",
|
484 |
+
"463": "PART|r-parataxis",
|
485 |
+
"464": "PART|r-xcomp",
|
486 |
+
"465": "PART|root",
|
487 |
+
"466": "PRON|Person=1|PronType=Prs",
|
488 |
+
"467": "PRON|Person=1|PronType=Prs|l-acl",
|
489 |
+
"468": "PRON|Person=1|PronType=Prs|l-advcl",
|
490 |
+
"469": "PRON|Person=1|PronType=Prs|l-det",
|
491 |
+
"470": "PRON|Person=1|PronType=Prs|l-iobj",
|
492 |
+
"471": "PRON|Person=1|PronType=Prs|l-nsubj",
|
493 |
+
"472": "PRON|Person=1|PronType=Prs|l-nsubj:outer",
|
494 |
+
"473": "PRON|Person=1|PronType=Prs|l-obj",
|
495 |
+
"474": "PRON|Person=1|PronType=Prs|l-obl",
|
496 |
+
"475": "PRON|Person=1|PronType=Prs|l-vocative",
|
497 |
+
"476": "PRON|Person=1|PronType=Prs|r-ccomp",
|
498 |
+
"477": "PRON|Person=1|PronType=Prs|r-conj",
|
499 |
+
"478": "PRON|Person=1|PronType=Prs|r-iobj",
|
500 |
+
"479": "PRON|Person=1|PronType=Prs|r-nsubj",
|
501 |
+
"480": "PRON|Person=1|PronType=Prs|r-obj",
|
502 |
+
"481": "PRON|Person=1|PronType=Prs|r-obl",
|
503 |
+
"482": "PRON|Person=1|PronType=Prs|r-obl:lmod",
|
504 |
+
"483": "PRON|Person=1|PronType=Prs|root",
|
505 |
+
"484": "PRON|Person=2|PronType=Prs",
|
506 |
+
"485": "PRON|Person=2|PronType=Prs|l-advcl",
|
507 |
+
"486": "PRON|Person=2|PronType=Prs|l-amod",
|
508 |
+
"487": "PRON|Person=2|PronType=Prs|l-det",
|
509 |
+
"488": "PRON|Person=2|PronType=Prs|l-nsubj",
|
510 |
+
"489": "PRON|Person=2|PronType=Prs|l-nsubj:outer",
|
511 |
+
"490": "PRON|Person=2|PronType=Prs|l-obj",
|
512 |
+
"491": "PRON|Person=2|PronType=Prs|l-obl",
|
513 |
+
"492": "PRON|Person=2|PronType=Prs|l-vocative",
|
514 |
+
"493": "PRON|Person=2|PronType=Prs|r-conj",
|
515 |
+
"494": "PRON|Person=2|PronType=Prs|r-flat",
|
516 |
+
"495": "PRON|Person=2|PronType=Prs|r-iobj",
|
517 |
+
"496": "PRON|Person=2|PronType=Prs|r-obj",
|
518 |
+
"497": "PRON|Person=2|PronType=Prs|r-obl",
|
519 |
+
"498": "PRON|Person=2|PronType=Prs|root",
|
520 |
+
"499": "PRON|Person=3|PronType=Prs",
|
521 |
+
"500": "PRON|Person=3|PronType=Prs|l-advcl",
|
522 |
+
"501": "PRON|Person=3|PronType=Prs|l-amod",
|
523 |
+
"502": "PRON|Person=3|PronType=Prs|l-det",
|
524 |
+
"503": "PRON|Person=3|PronType=Prs|l-dislocated",
|
525 |
+
"504": "PRON|Person=3|PronType=Prs|l-expl",
|
526 |
+
"505": "PRON|Person=3|PronType=Prs|l-iobj",
|
527 |
+
"506": "PRON|Person=3|PronType=Prs|l-nsubj",
|
528 |
+
"507": "PRON|Person=3|PronType=Prs|l-nsubj:outer",
|
529 |
+
"508": "PRON|Person=3|PronType=Prs|l-nsubj:pass",
|
530 |
+
"509": "PRON|Person=3|PronType=Prs|l-obj",
|
531 |
+
"510": "PRON|Person=3|PronType=Prs|l-obl",
|
532 |
+
"511": "PRON|Person=3|PronType=Prs|r-ccomp",
|
533 |
+
"512": "PRON|Person=3|PronType=Prs|r-conj",
|
534 |
+
"513": "PRON|Person=3|PronType=Prs|r-expl",
|
535 |
+
"514": "PRON|Person=3|PronType=Prs|r-iobj",
|
536 |
+
"515": "PRON|Person=3|PronType=Prs|r-nsubj",
|
537 |
+
"516": "PRON|Person=3|PronType=Prs|r-obj",
|
538 |
+
"517": "PRON|Person=3|PronType=Prs|r-obl",
|
539 |
+
"518": "PRON|Person=3|PronType=Prs|root",
|
540 |
+
"519": "PRON|PronType=Dem",
|
541 |
+
"520": "PRON|PronType=Dem|l-acl",
|
542 |
+
"521": "PRON|PronType=Dem|l-advcl",
|
543 |
+
"522": "PRON|PronType=Dem|l-amod",
|
544 |
+
"523": "PRON|PronType=Dem|l-compound",
|
545 |
+
"524": "PRON|PronType=Dem|l-det",
|
546 |
+
"525": "PRON|PronType=Dem|l-dislocated",
|
547 |
+
"526": "PRON|PronType=Dem|l-expl",
|
548 |
+
"527": "PRON|PronType=Dem|l-nsubj",
|
549 |
+
"528": "PRON|PronType=Dem|l-nsubj:outer",
|
550 |
+
"529": "PRON|PronType=Dem|l-obj",
|
551 |
+
"530": "PRON|PronType=Dem|l-obl",
|
552 |
+
"531": "PRON|PronType=Dem|l-obl:lmod",
|
553 |
+
"532": "PRON|PronType=Dem|r-conj",
|
554 |
+
"533": "PRON|PronType=Dem|r-det",
|
555 |
+
"534": "PRON|PronType=Dem|r-expl",
|
556 |
+
"535": "PRON|PronType=Dem|r-flat",
|
557 |
+
"536": "PRON|PronType=Dem|r-iobj",
|
558 |
+
"537": "PRON|PronType=Dem|r-obj",
|
559 |
+
"538": "PRON|PronType=Dem|r-obl",
|
560 |
+
"539": "PRON|PronType=Dem|r-obl:lmod",
|
561 |
+
"540": "PRON|PronType=Dem|root",
|
562 |
+
"541": "PRON|PronType=Int",
|
563 |
+
"542": "PRON|PronType=Int|l-advcl",
|
564 |
+
"543": "PRON|PronType=Int|l-amod",
|
565 |
+
"544": "PRON|PronType=Int|l-det",
|
566 |
+
"545": "PRON|PronType=Int|l-dislocated",
|
567 |
+
"546": "PRON|PronType=Int|l-nsubj",
|
568 |
+
"547": "PRON|PronType=Int|l-nsubj:outer",
|
569 |
+
"548": "PRON|PronType=Int|l-obj",
|
570 |
+
"549": "PRON|PronType=Int|l-obl",
|
571 |
+
"550": "PRON|PronType=Int|l-vocative",
|
572 |
+
"551": "PRON|PronType=Int|r-ccomp",
|
573 |
+
"552": "PRON|PronType=Int|r-conj",
|
574 |
+
"553": "PRON|PronType=Int|r-flat",
|
575 |
+
"554": "PRON|PronType=Int|r-obj",
|
576 |
+
"555": "PRON|PronType=Int|r-parataxis",
|
577 |
+
"556": "PRON|PronType=Int|r-xcomp",
|
578 |
+
"557": "PRON|PronType=Int|root",
|
579 |
+
"558": "PRON|PronType=Prs",
|
580 |
+
"559": "PRON|PronType=Prs|Reflex=Yes",
|
581 |
+
"560": "PRON|PronType=Prs|Reflex=Yes|l-acl",
|
582 |
+
"561": "PRON|PronType=Prs|Reflex=Yes|l-det",
|
583 |
+
"562": "PRON|PronType=Prs|Reflex=Yes|l-nsubj",
|
584 |
+
"563": "PRON|PronType=Prs|Reflex=Yes|l-obj",
|
585 |
+
"564": "PRON|PronType=Prs|Reflex=Yes|l-obl",
|
586 |
+
"565": "PRON|PronType=Prs|Reflex=Yes|r-dislocated",
|
587 |
+
"566": "PRON|PronType=Prs|Reflex=Yes|r-obj",
|
588 |
+
"567": "PRON|PronType=Prs|Reflex=Yes|r-obl",
|
589 |
+
"568": "PRON|PronType=Prs|Reflex=Yes|root",
|
590 |
+
"569": "PRON|PronType=Prs|l-det",
|
591 |
+
"570": "PRON|PronType=Prs|l-nsubj",
|
592 |
+
"571": "PRON|PronType=Prs|l-nsubj:outer",
|
593 |
+
"572": "PRON|PronType=Prs|l-obj",
|
594 |
+
"573": "PRON|PronType=Prs|r-conj",
|
595 |
+
"574": "PRON|PronType=Prs|r-iobj",
|
596 |
+
"575": "PRON|PronType=Prs|r-obj",
|
597 |
+
"576": "PROPN",
|
598 |
+
"577": "PROPN|Case=Loc|NameType=Geo",
|
599 |
+
"578": "PROPN|Case=Loc|NameType=Geo|l-acl",
|
600 |
+
"579": "PROPN|Case=Loc|NameType=Geo|l-advcl",
|
601 |
+
"580": "PROPN|Case=Loc|NameType=Geo|l-amod",
|
602 |
+
"581": "PROPN|Case=Loc|NameType=Geo|l-compound",
|
603 |
+
"582": "PROPN|Case=Loc|NameType=Geo|l-csubj",
|
604 |
+
"583": "PROPN|Case=Loc|NameType=Geo|l-dislocated",
|
605 |
+
"584": "PROPN|Case=Loc|NameType=Geo|l-nmod",
|
606 |
+
"585": "PROPN|Case=Loc|NameType=Geo|l-nsubj",
|
607 |
+
"586": "PROPN|Case=Loc|NameType=Geo|l-nsubj:outer",
|
608 |
+
"587": "PROPN|Case=Loc|NameType=Geo|l-obl",
|
609 |
+
"588": "PROPN|Case=Loc|NameType=Geo|l-obl:lmod",
|
610 |
+
"589": "PROPN|Case=Loc|NameType=Geo|r-conj",
|
611 |
+
"590": "PROPN|Case=Loc|NameType=Geo|r-flat",
|
612 |
+
"591": "PROPN|Case=Loc|NameType=Geo|r-iobj",
|
613 |
+
"592": "PROPN|Case=Loc|NameType=Geo|r-obj",
|
614 |
+
"593": "PROPN|Case=Loc|NameType=Geo|r-obl",
|
615 |
+
"594": "PROPN|Case=Loc|NameType=Geo|r-obl:lmod",
|
616 |
+
"595": "PROPN|Case=Loc|NameType=Geo|r-parataxis",
|
617 |
+
"596": "PROPN|Case=Loc|NameType=Geo|r-xcomp",
|
618 |
+
"597": "PROPN|Case=Loc|NameType=Geo|root",
|
619 |
+
"598": "PROPN|Case=Loc|NameType=Nat",
|
620 |
+
"599": "PROPN|Case=Loc|NameType=Nat|l-acl",
|
621 |
+
"600": "PROPN|Case=Loc|NameType=Nat|l-advcl",
|
622 |
+
"601": "PROPN|Case=Loc|NameType=Nat|l-amod",
|
623 |
+
"602": "PROPN|Case=Loc|NameType=Nat|l-clf",
|
624 |
+
"603": "PROPN|Case=Loc|NameType=Nat|l-compound",
|
625 |
+
"604": "PROPN|Case=Loc|NameType=Nat|l-nmod",
|
626 |
+
"605": "PROPN|Case=Loc|NameType=Nat|l-nsubj",
|
627 |
+
"606": "PROPN|Case=Loc|NameType=Nat|l-nsubj:outer",
|
628 |
+
"607": "PROPN|Case=Loc|NameType=Nat|l-nsubj:pass",
|
629 |
+
"608": "PROPN|Case=Loc|NameType=Nat|l-obj",
|
630 |
+
"609": "PROPN|Case=Loc|NameType=Nat|l-obl",
|
631 |
+
"610": "PROPN|Case=Loc|NameType=Nat|l-obl:lmod",
|
632 |
+
"611": "PROPN|Case=Loc|NameType=Nat|r-ccomp",
|
633 |
+
"612": "PROPN|Case=Loc|NameType=Nat|r-conj",
|
634 |
+
"613": "PROPN|Case=Loc|NameType=Nat|r-flat",
|
635 |
+
"614": "PROPN|Case=Loc|NameType=Nat|r-iobj",
|
636 |
+
"615": "PROPN|Case=Loc|NameType=Nat|r-nmod",
|
637 |
+
"616": "PROPN|Case=Loc|NameType=Nat|r-obj",
|
638 |
+
"617": "PROPN|Case=Loc|NameType=Nat|r-obl",
|
639 |
+
"618": "PROPN|Case=Loc|NameType=Nat|r-obl:lmod",
|
640 |
+
"619": "PROPN|Case=Loc|NameType=Nat|r-parataxis",
|
641 |
+
"620": "PROPN|Case=Loc|NameType=Nat|r-xcomp",
|
642 |
+
"621": "PROPN|Case=Loc|NameType=Nat|root",
|
643 |
+
"622": "PROPN|NameType=Giv",
|
644 |
+
"623": "PROPN|NameType=Giv|l-acl",
|
645 |
+
"624": "PROPN|NameType=Giv|l-advcl",
|
646 |
+
"625": "PROPN|NameType=Giv|l-amod",
|
647 |
+
"626": "PROPN|NameType=Giv|l-compound",
|
648 |
+
"627": "PROPN|NameType=Giv|l-dislocated",
|
649 |
+
"628": "PROPN|NameType=Giv|l-nmod",
|
650 |
+
"629": "PROPN|NameType=Giv|l-nsubj",
|
651 |
+
"630": "PROPN|NameType=Giv|l-nsubj:outer",
|
652 |
+
"631": "PROPN|NameType=Giv|l-nsubj:pass",
|
653 |
+
"632": "PROPN|NameType=Giv|l-obj",
|
654 |
+
"633": "PROPN|NameType=Giv|l-obl",
|
655 |
+
"634": "PROPN|NameType=Giv|l-obl:lmod",
|
656 |
+
"635": "PROPN|NameType=Giv|l-parataxis",
|
657 |
+
"636": "PROPN|NameType=Giv|l-vocative",
|
658 |
+
"637": "PROPN|NameType=Giv|r-ccomp",
|
659 |
+
"638": "PROPN|NameType=Giv|r-conj",
|
660 |
+
"639": "PROPN|NameType=Giv|r-dislocated",
|
661 |
+
"640": "PROPN|NameType=Giv|r-flat",
|
662 |
+
"641": "PROPN|NameType=Giv|r-iobj",
|
663 |
+
"642": "PROPN|NameType=Giv|r-list",
|
664 |
+
"643": "PROPN|NameType=Giv|r-nmod",
|
665 |
+
"644": "PROPN|NameType=Giv|r-obj",
|
666 |
+
"645": "PROPN|NameType=Giv|r-obl",
|
667 |
+
"646": "PROPN|NameType=Giv|r-obl:lmod",
|
668 |
+
"647": "PROPN|NameType=Giv|r-parataxis",
|
669 |
+
"648": "PROPN|NameType=Giv|r-xcomp",
|
670 |
+
"649": "PROPN|NameType=Giv|root",
|
671 |
+
"650": "PROPN|NameType=Prs",
|
672 |
+
"651": "PROPN|NameType=Prs|l-acl",
|
673 |
+
"652": "PROPN|NameType=Prs|l-advcl",
|
674 |
+
"653": "PROPN|NameType=Prs|l-amod",
|
675 |
+
"654": "PROPN|NameType=Prs|l-compound",
|
676 |
+
"655": "PROPN|NameType=Prs|l-dislocated",
|
677 |
+
"656": "PROPN|NameType=Prs|l-nmod",
|
678 |
+
"657": "PROPN|NameType=Prs|l-nsubj",
|
679 |
+
"658": "PROPN|NameType=Prs|l-nsubj:outer",
|
680 |
+
"659": "PROPN|NameType=Prs|l-obj",
|
681 |
+
"660": "PROPN|NameType=Prs|l-obl",
|
682 |
+
"661": "PROPN|NameType=Prs|r-conj",
|
683 |
+
"662": "PROPN|NameType=Prs|r-dislocated",
|
684 |
+
"663": "PROPN|NameType=Prs|r-flat",
|
685 |
+
"664": "PROPN|NameType=Prs|r-iobj",
|
686 |
+
"665": "PROPN|NameType=Prs|r-obj",
|
687 |
+
"666": "PROPN|NameType=Prs|r-obl",
|
688 |
+
"667": "PROPN|NameType=Prs|r-parataxis",
|
689 |
+
"668": "PROPN|NameType=Prs|root",
|
690 |
+
"669": "PROPN|NameType=Sur",
|
691 |
+
"670": "PROPN|NameType=Sur|l-acl",
|
692 |
+
"671": "PROPN|NameType=Sur|l-advcl",
|
693 |
+
"672": "PROPN|NameType=Sur|l-amod",
|
694 |
+
"673": "PROPN|NameType=Sur|l-compound",
|
695 |
+
"674": "PROPN|NameType=Sur|l-csubj",
|
696 |
+
"675": "PROPN|NameType=Sur|l-dislocated",
|
697 |
+
"676": "PROPN|NameType=Sur|l-nmod",
|
698 |
+
"677": "PROPN|NameType=Sur|l-nsubj",
|
699 |
+
"678": "PROPN|NameType=Sur|l-nsubj:outer",
|
700 |
+
"679": "PROPN|NameType=Sur|l-nsubj:pass",
|
701 |
+
"680": "PROPN|NameType=Sur|l-obl",
|
702 |
+
"681": "PROPN|NameType=Sur|l-obl:lmod",
|
703 |
+
"682": "PROPN|NameType=Sur|l-vocative",
|
704 |
+
"683": "PROPN|NameType=Sur|r-ccomp",
|
705 |
+
"684": "PROPN|NameType=Sur|r-conj",
|
706 |
+
"685": "PROPN|NameType=Sur|r-dislocated",
|
707 |
+
"686": "PROPN|NameType=Sur|r-flat",
|
708 |
+
"687": "PROPN|NameType=Sur|r-iobj",
|
709 |
+
"688": "PROPN|NameType=Sur|r-list",
|
710 |
+
"689": "PROPN|NameType=Sur|r-nmod",
|
711 |
+
"690": "PROPN|NameType=Sur|r-nsubj",
|
712 |
+
"691": "PROPN|NameType=Sur|r-obj",
|
713 |
+
"692": "PROPN|NameType=Sur|r-obl",
|
714 |
+
"693": "PROPN|NameType=Sur|r-obl:lmod",
|
715 |
+
"694": "PROPN|NameType=Sur|r-parataxis",
|
716 |
+
"695": "PROPN|NameType=Sur|r-xcomp",
|
717 |
+
"696": "PROPN|NameType=Sur|root",
|
718 |
+
"697": "PROPN|l-nmod",
|
719 |
+
"698": "PUNCT",
|
720 |
+
"699": "PUNCT|root",
|
721 |
+
"700": "SCONJ",
|
722 |
+
"701": "SCONJ|l-case",
|
723 |
+
"702": "SCONJ|l-cc",
|
724 |
+
"703": "SCONJ|l-mark",
|
725 |
+
"704": "SCONJ|l-nsubj",
|
726 |
+
"705": "SCONJ|l-obl",
|
727 |
+
"706": "SCONJ|r-case",
|
728 |
+
"707": "SCONJ|r-iobj",
|
729 |
+
"708": "SCONJ|r-mark",
|
730 |
+
"709": "SCONJ|r-nsubj",
|
731 |
+
"710": "SCONJ|r-nsubj:pass",
|
732 |
+
"711": "SCONJ|r-obj",
|
733 |
+
"712": "SCONJ|root",
|
734 |
+
"713": "SYM",
|
735 |
+
"714": "SYM|l-nmod",
|
736 |
+
"715": "SYM|l-nsubj",
|
737 |
+
"716": "SYM|r-conj",
|
738 |
+
"717": "SYM|r-nmod",
|
739 |
+
"718": "SYM|r-xcomp",
|
740 |
+
"719": "SYM|root",
|
741 |
+
"720": "VERB",
|
742 |
+
"721": "VERB|Degree=Equ",
|
743 |
+
"722": "VERB|Degree=Equ|VerbForm=Part",
|
744 |
+
"723": "VERB|Degree=Equ|VerbForm=Part|l-amod",
|
745 |
+
"724": "VERB|Degree=Equ|l-acl",
|
746 |
+
"725": "VERB|Degree=Equ|l-advcl",
|
747 |
+
"726": "VERB|Degree=Equ|l-ccomp",
|
748 |
+
"727": "VERB|Degree=Equ|l-csubj",
|
749 |
+
"728": "VERB|Degree=Equ|l-nsubj",
|
750 |
+
"729": "VERB|Degree=Equ|l-obj",
|
751 |
+
"730": "VERB|Degree=Equ|r-ccomp",
|
752 |
+
"731": "VERB|Degree=Equ|r-compound:redup",
|
753 |
+
"732": "VERB|Degree=Equ|r-conj",
|
754 |
+
"733": "VERB|Degree=Equ|r-obj",
|
755 |
+
"734": "VERB|Degree=Equ|r-parataxis",
|
756 |
+
"735": "VERB|Degree=Equ|r-xcomp",
|
757 |
+
"736": "VERB|Degree=Equ|root",
|
758 |
+
"737": "VERB|Degree=Pos",
|
759 |
+
"738": "VERB|Degree=Pos|VerbForm=Part",
|
760 |
+
"739": "VERB|Degree=Pos|VerbForm=Part|l-amod",
|
761 |
+
"740": "VERB|Degree=Pos|VerbForm=Part|r-amod",
|
762 |
+
"741": "VERB|Degree=Pos|l-acl",
|
763 |
+
"742": "VERB|Degree=Pos|l-advcl",
|
764 |
+
"743": "VERB|Degree=Pos|l-ccomp",
|
765 |
+
"744": "VERB|Degree=Pos|l-csubj",
|
766 |
+
"745": "VERB|Degree=Pos|l-csubj:outer",
|
767 |
+
"746": "VERB|Degree=Pos|l-dislocated",
|
768 |
+
"747": "VERB|Degree=Pos|l-nsubj",
|
769 |
+
"748": "VERB|Degree=Pos|l-nsubj:outer",
|
770 |
+
"749": "VERB|Degree=Pos|l-obj",
|
771 |
+
"750": "VERB|Degree=Pos|l-obl",
|
772 |
+
"751": "VERB|Degree=Pos|l-vocative",
|
773 |
+
"752": "VERB|Degree=Pos|r-advcl",
|
774 |
+
"753": "VERB|Degree=Pos|r-ccomp",
|
775 |
+
"754": "VERB|Degree=Pos|r-compound:redup",
|
776 |
+
"755": "VERB|Degree=Pos|r-conj",
|
777 |
+
"756": "VERB|Degree=Pos|r-dislocated",
|
778 |
+
"757": "VERB|Degree=Pos|r-fixed",
|
779 |
+
"758": "VERB|Degree=Pos|r-flat:vv",
|
780 |
+
"759": "VERB|Degree=Pos|r-iobj",
|
781 |
+
"760": "VERB|Degree=Pos|r-obj",
|
782 |
+
"761": "VERB|Degree=Pos|r-obl",
|
783 |
+
"762": "VERB|Degree=Pos|r-parataxis",
|
784 |
+
"763": "VERB|Degree=Pos|r-xcomp",
|
785 |
+
"764": "VERB|Degree=Pos|root",
|
786 |
+
"765": "VERB|Polarity=Neg",
|
787 |
+
"766": "VERB|Polarity=Neg|VerbForm=Part",
|
788 |
+
"767": "VERB|Polarity=Neg|VerbForm=Part|l-amod",
|
789 |
+
"768": "VERB|Polarity=Neg|l-acl",
|
790 |
+
"769": "VERB|Polarity=Neg|l-advcl",
|
791 |
+
"770": "VERB|Polarity=Neg|l-ccomp",
|
792 |
+
"771": "VERB|Polarity=Neg|l-csubj",
|
793 |
+
"772": "VERB|Polarity=Neg|l-csubj:outer",
|
794 |
+
"773": "VERB|Polarity=Neg|l-nsubj",
|
795 |
+
"774": "VERB|Polarity=Neg|l-obl",
|
796 |
+
"775": "VERB|Polarity=Neg|r-advcl",
|
797 |
+
"776": "VERB|Polarity=Neg|r-ccomp",
|
798 |
+
"777": "VERB|Polarity=Neg|r-conj",
|
799 |
+
"778": "VERB|Polarity=Neg|r-flat:vv",
|
800 |
+
"779": "VERB|Polarity=Neg|r-obj",
|
801 |
+
"780": "VERB|Polarity=Neg|r-obl",
|
802 |
+
"781": "VERB|Polarity=Neg|r-parataxis",
|
803 |
+
"782": "VERB|Polarity=Neg|r-xcomp",
|
804 |
+
"783": "VERB|Polarity=Neg|root",
|
805 |
+
"784": "VERB|VerbForm=Part",
|
806 |
+
"785": "VERB|VerbForm=Part|l-amod",
|
807 |
+
"786": "VERB|VerbForm=Part|r-amod",
|
808 |
+
"787": "VERB|l-acl",
|
809 |
+
"788": "VERB|l-advcl",
|
810 |
+
"789": "VERB|l-ccomp",
|
811 |
+
"790": "VERB|l-csubj",
|
812 |
+
"791": "VERB|l-csubj:outer",
|
813 |
+
"792": "VERB|l-csubj:pass",
|
814 |
+
"793": "VERB|l-dislocated",
|
815 |
+
"794": "VERB|l-nsubj",
|
816 |
+
"795": "VERB|l-nsubj:outer",
|
817 |
+
"796": "VERB|l-obj",
|
818 |
+
"797": "VERB|l-obl",
|
819 |
+
"798": "VERB|l-obl:lmod",
|
820 |
+
"799": "VERB|l-parataxis",
|
821 |
+
"800": "VERB|r-acl",
|
822 |
+
"801": "VERB|r-advcl",
|
823 |
+
"802": "VERB|r-ccomp",
|
824 |
+
"803": "VERB|r-compound:redup",
|
825 |
+
"804": "VERB|r-conj",
|
826 |
+
"805": "VERB|r-dislocated",
|
827 |
+
"806": "VERB|r-fixed",
|
828 |
+
"807": "VERB|r-flat:vv",
|
829 |
+
"808": "VERB|r-iobj",
|
830 |
+
"809": "VERB|r-list",
|
831 |
+
"810": "VERB|r-obj",
|
832 |
+
"811": "VERB|r-obl",
|
833 |
+
"812": "VERB|r-obl:lmod",
|
834 |
+
"813": "VERB|r-parataxis",
|
835 |
+
"814": "VERB|r-vocative",
|
836 |
+
"815": "VERB|r-xcomp",
|
837 |
+
"816": "VERB|root"
|
838 |
+
},
|
839 |
+
"initializer_range": 0.02,
|
840 |
+
"intermediate_size": 8960,
|
841 |
+
"label2id": {
|
842 |
+
"ADP": 0,
|
843 |
+
"ADP|Degree=Equ": 1,
|
844 |
+
"ADP|Degree=Equ|l-cc": 2,
|
845 |
+
"ADP|l-acl": 3,
|
846 |
+
"ADP|l-advcl": 4,
|
847 |
+
"ADP|l-amod": 5,
|
848 |
+
"ADP|l-case": 6,
|
849 |
+
"ADP|l-cc": 7,
|
850 |
+
"ADP|l-mark": 8,
|
851 |
+
"ADP|l-nsubj": 9,
|
852 |
+
"ADP|l-obl": 10,
|
853 |
+
"ADP|r-case": 11,
|
854 |
+
"ADP|r-conj": 12,
|
855 |
+
"ADP|r-fixed": 13,
|
856 |
+
"ADP|r-mark": 14,
|
857 |
+
"ADP|r-obj": 15,
|
858 |
+
"ADP|root": 16,
|
859 |
+
"ADV": 17,
|
860 |
+
"ADV|AdvType=Cau": 18,
|
861 |
+
"ADV|AdvType=Cau|l-advmod": 19,
|
862 |
+
"ADV|AdvType=Cau|l-amod": 20,
|
863 |
+
"ADV|AdvType=Cau|l-nsubj": 21,
|
864 |
+
"ADV|AdvType=Cau|l-obj": 22,
|
865 |
+
"ADV|AdvType=Deg|Degree=Cmp": 23,
|
866 |
+
"ADV|AdvType=Deg|Degree=Cmp|l-advmod": 24,
|
867 |
+
"ADV|AdvType=Deg|Degree=Cmp|l-amod": 25,
|
868 |
+
"ADV|AdvType=Deg|Degree=Cmp|r-conj": 26,
|
869 |
+
"ADV|AdvType=Deg|Degree=Cmp|r-obj": 27,
|
870 |
+
"ADV|AdvType=Deg|Degree=Pos": 28,
|
871 |
+
"ADV|AdvType=Deg|Degree=Pos|l-advmod": 29,
|
872 |
+
"ADV|AdvType=Deg|Degree=Pos|l-amod": 30,
|
873 |
+
"ADV|AdvType=Deg|Degree=Pos|r-ccomp": 31,
|
874 |
+
"ADV|AdvType=Deg|Degree=Pos|r-conj": 32,
|
875 |
+
"ADV|AdvType=Deg|Degree=Pos|r-flat:vv": 33,
|
876 |
+
"ADV|AdvType=Deg|Degree=Pos|r-parataxis": 34,
|
877 |
+
"ADV|AdvType=Deg|Degree=Pos|root": 35,
|
878 |
+
"ADV|AdvType=Deg|Degree=Sup": 36,
|
879 |
+
"ADV|AdvType=Deg|Degree=Sup|l-advmod": 37,
|
880 |
+
"ADV|AdvType=Deg|Degree=Sup|l-amod": 38,
|
881 |
+
"ADV|AdvType=Deg|Degree=Sup|l-nsubj": 39,
|
882 |
+
"ADV|AdvType=Deg|Degree=Sup|r-conj": 40,
|
883 |
+
"ADV|AdvType=Deg|Degree=Sup|r-parataxis": 41,
|
884 |
+
"ADV|AdvType=Deg|Degree=Sup|root": 42,
|
885 |
+
"ADV|AdvType=Tim": 43,
|
886 |
+
"ADV|AdvType=Tim|Aspect=Perf": 44,
|
887 |
+
"ADV|AdvType=Tim|Aspect=Perf|l-advmod": 45,
|
888 |
+
"ADV|AdvType=Tim|Aspect=Perf|l-amod": 46,
|
889 |
+
"ADV|AdvType=Tim|Aspect=Perf|l-obl:lmod": 47,
|
890 |
+
"ADV|AdvType=Tim|Aspect=Perf|r-parataxis": 48,
|
891 |
+
"ADV|AdvType=Tim|Aspect=Perf|root": 49,
|
892 |
+
"ADV|AdvType=Tim|Tense=Fut": 50,
|
893 |
+
"ADV|AdvType=Tim|Tense=Fut|l-advmod": 51,
|
894 |
+
"ADV|AdvType=Tim|Tense=Fut|l-amod": 52,
|
895 |
+
"ADV|AdvType=Tim|Tense=Fut|l-nsubj": 53,
|
896 |
+
"ADV|AdvType=Tim|Tense=Fut|l-nsubj:outer": 54,
|
897 |
+
"ADV|AdvType=Tim|Tense=Fut|root": 55,
|
898 |
+
"ADV|AdvType=Tim|Tense=Past": 56,
|
899 |
+
"ADV|AdvType=Tim|Tense=Past|l-advmod": 57,
|
900 |
+
"ADV|AdvType=Tim|Tense=Past|l-amod": 58,
|
901 |
+
"ADV|AdvType=Tim|Tense=Pres": 59,
|
902 |
+
"ADV|AdvType=Tim|Tense=Pres|l-advmod": 60,
|
903 |
+
"ADV|AdvType=Tim|Tense=Pres|l-amod": 61,
|
904 |
+
"ADV|AdvType=Tim|Tense=Pres|root": 62,
|
905 |
+
"ADV|AdvType=Tim|l-advcl": 63,
|
906 |
+
"ADV|AdvType=Tim|l-advmod": 64,
|
907 |
+
"ADV|AdvType=Tim|l-amod": 65,
|
908 |
+
"ADV|AdvType=Tim|l-nsubj": 66,
|
909 |
+
"ADV|AdvType=Tim|r-advmod": 67,
|
910 |
+
"ADV|AdvType=Tim|r-ccomp": 68,
|
911 |
+
"ADV|AdvType=Tim|r-compound:redup": 69,
|
912 |
+
"ADV|AdvType=Tim|r-conj": 70,
|
913 |
+
"ADV|AdvType=Tim|r-flat:vv": 71,
|
914 |
+
"ADV|AdvType=Tim|r-parataxis": 72,
|
915 |
+
"ADV|AdvType=Tim|root": 73,
|
916 |
+
"ADV|Degree=Equ|VerbForm=Conv": 74,
|
917 |
+
"ADV|Degree=Equ|VerbForm=Conv|l-advmod": 75,
|
918 |
+
"ADV|Degree=Pos|VerbForm=Conv": 76,
|
919 |
+
"ADV|Degree=Pos|VerbForm=Conv|l-advmod": 77,
|
920 |
+
"ADV|Degree=Pos|VerbForm=Conv|r-advmod": 78,
|
921 |
+
"ADV|Polarity=Neg": 79,
|
922 |
+
"ADV|Polarity=Neg|VerbForm=Conv": 80,
|
923 |
+
"ADV|Polarity=Neg|VerbForm=Conv|l-advmod": 81,
|
924 |
+
"ADV|Polarity=Neg|l-advmod": 82,
|
925 |
+
"ADV|Polarity=Neg|l-amod": 83,
|
926 |
+
"ADV|Polarity=Neg|l-nsubj": 84,
|
927 |
+
"ADV|Polarity=Neg|l-parataxis": 85,
|
928 |
+
"ADV|Polarity=Neg|r-advmod": 86,
|
929 |
+
"ADV|Polarity=Neg|r-conj": 87,
|
930 |
+
"ADV|Polarity=Neg|r-obj": 88,
|
931 |
+
"ADV|Polarity=Neg|r-parataxis": 89,
|
932 |
+
"ADV|Polarity=Neg|root": 90,
|
933 |
+
"ADV|VerbForm=Conv": 91,
|
934 |
+
"ADV|VerbForm=Conv|l-advmod": 92,
|
935 |
+
"ADV|VerbForm=Conv|r-advmod": 93,
|
936 |
+
"ADV|l-acl": 94,
|
937 |
+
"ADV|l-advcl": 95,
|
938 |
+
"ADV|l-advmod": 96,
|
939 |
+
"ADV|l-amod": 97,
|
940 |
+
"ADV|l-cc": 98,
|
941 |
+
"ADV|l-nsubj": 99,
|
942 |
+
"ADV|r-advmod": 100,
|
943 |
+
"ADV|r-ccomp": 101,
|
944 |
+
"ADV|r-conj": 102,
|
945 |
+
"ADV|r-flat:vv": 103,
|
946 |
+
"ADV|r-obj": 104,
|
947 |
+
"ADV|root": 105,
|
948 |
+
"AUX|Mood=Des": 106,
|
949 |
+
"AUX|Mood=Des|l-aux": 107,
|
950 |
+
"AUX|Mood=Des|l-csubj": 108,
|
951 |
+
"AUX|Mood=Des|l-parataxis": 109,
|
952 |
+
"AUX|Mood=Des|r-ccomp": 110,
|
953 |
+
"AUX|Mood=Des|r-conj": 111,
|
954 |
+
"AUX|Mood=Des|r-flat:vv": 112,
|
955 |
+
"AUX|Mood=Des|root": 113,
|
956 |
+
"AUX|Mood=Nec": 114,
|
957 |
+
"AUX|Mood=Nec|l-acl": 115,
|
958 |
+
"AUX|Mood=Nec|l-amod": 116,
|
959 |
+
"AUX|Mood=Nec|l-aux": 117,
|
960 |
+
"AUX|Mood=Nec|r-aux": 118,
|
961 |
+
"AUX|Mood=Nec|root": 119,
|
962 |
+
"AUX|Mood=Pot": 120,
|
963 |
+
"AUX|Mood=Pot|l-acl": 121,
|
964 |
+
"AUX|Mood=Pot|l-advcl": 122,
|
965 |
+
"AUX|Mood=Pot|l-amod": 123,
|
966 |
+
"AUX|Mood=Pot|l-aux": 124,
|
967 |
+
"AUX|Mood=Pot|l-csubj": 125,
|
968 |
+
"AUX|Mood=Pot|l-nsubj": 126,
|
969 |
+
"AUX|Mood=Pot|r-ccomp": 127,
|
970 |
+
"AUX|Mood=Pot|r-conj": 128,
|
971 |
+
"AUX|Mood=Pot|r-obj": 129,
|
972 |
+
"AUX|Mood=Pot|r-parataxis": 130,
|
973 |
+
"AUX|Mood=Pot|r-xcomp": 131,
|
974 |
+
"AUX|Mood=Pot|root": 132,
|
975 |
+
"AUX|VerbType=Cop": 133,
|
976 |
+
"AUX|VerbType=Cop|l-cop": 134,
|
977 |
+
"AUX|Voice=Pass": 135,
|
978 |
+
"AUX|Voice=Pass|l-aux": 136,
|
979 |
+
"AUX|Voice=Pass|r-conj": 137,
|
980 |
+
"AUX|Voice=Pass|root": 138,
|
981 |
+
"B-ADP": 139,
|
982 |
+
"B-ADP|Degree=Equ": 140,
|
983 |
+
"B-ADV": 141,
|
984 |
+
"B-ADV|AdvType=Cau": 142,
|
985 |
+
"B-ADV|AdvType=Deg|Degree=Cmp": 143,
|
986 |
+
"B-ADV|AdvType=Deg|Degree=Pos": 144,
|
987 |
+
"B-ADV|AdvType=Deg|Degree=Sup": 145,
|
988 |
+
"B-ADV|AdvType=Tim": 146,
|
989 |
+
"B-ADV|AdvType=Tim|Aspect=Perf": 147,
|
990 |
+
"B-ADV|AdvType=Tim|Tense=Fut": 148,
|
991 |
+
"B-ADV|AdvType=Tim|Tense=Past": 149,
|
992 |
+
"B-ADV|AdvType=Tim|Tense=Pres": 150,
|
993 |
+
"B-ADV|Degree=Equ|VerbForm=Conv": 151,
|
994 |
+
"B-ADV|Degree=Pos|VerbForm=Conv": 152,
|
995 |
+
"B-ADV|Polarity=Neg": 153,
|
996 |
+
"B-ADV|Polarity=Neg|VerbForm=Conv": 154,
|
997 |
+
"B-ADV|VerbForm=Conv": 155,
|
998 |
+
"B-AUX|Mood=Des": 156,
|
999 |
+
"B-AUX|Mood=Nec": 157,
|
1000 |
+
"B-AUX|Mood=Pot": 158,
|
1001 |
+
"B-AUX|VerbType=Cop": 159,
|
1002 |
+
"B-AUX|Voice=Pass": 160,
|
1003 |
+
"B-CCONJ": 161,
|
1004 |
+
"B-INTJ": 162,
|
1005 |
+
"B-NOUN": 163,
|
1006 |
+
"B-NOUN|Case=Loc": 164,
|
1007 |
+
"B-NOUN|Case=Tem": 165,
|
1008 |
+
"B-NOUN|Degree=Pos": 166,
|
1009 |
+
"B-NOUN|NounType=Clf": 167,
|
1010 |
+
"B-NUM": 168,
|
1011 |
+
"B-NUM|NumType=Ord": 169,
|
1012 |
+
"B-PART": 170,
|
1013 |
+
"B-PRON|Person=1|PronType=Prs": 171,
|
1014 |
+
"B-PRON|Person=2|PronType=Prs": 172,
|
1015 |
+
"B-PRON|Person=3|PronType=Prs": 173,
|
1016 |
+
"B-PRON|PronType=Dem": 174,
|
1017 |
+
"B-PRON|PronType=Int": 175,
|
1018 |
+
"B-PRON|PronType=Prs": 176,
|
1019 |
+
"B-PRON|PronType=Prs|Reflex=Yes": 177,
|
1020 |
+
"B-PROPN": 178,
|
1021 |
+
"B-PROPN|Case=Loc|NameType=Geo": 179,
|
1022 |
+
"B-PROPN|Case=Loc|NameType=Nat": 180,
|
1023 |
+
"B-PROPN|NameType=Giv": 181,
|
1024 |
+
"B-PROPN|NameType=Prs": 182,
|
1025 |
+
"B-PROPN|NameType=Sur": 183,
|
1026 |
+
"B-PUNCT": 184,
|
1027 |
+
"B-SCONJ": 185,
|
1028 |
+
"B-SYM": 186,
|
1029 |
+
"B-VERB": 187,
|
1030 |
+
"B-VERB|Degree=Equ": 188,
|
1031 |
+
"B-VERB|Degree=Equ|VerbForm=Part": 189,
|
1032 |
+
"B-VERB|Degree=Pos": 190,
|
1033 |
+
"B-VERB|Degree=Pos|VerbForm=Part": 191,
|
1034 |
+
"B-VERB|Polarity=Neg": 192,
|
1035 |
+
"B-VERB|Polarity=Neg|VerbForm=Part": 193,
|
1036 |
+
"B-VERB|VerbForm=Part": 194,
|
1037 |
+
"CCONJ": 195,
|
1038 |
+
"CCONJ|l-advmod": 196,
|
1039 |
+
"CCONJ|l-amod": 197,
|
1040 |
+
"CCONJ|l-cc": 198,
|
1041 |
+
"CCONJ|l-obj": 199,
|
1042 |
+
"CCONJ|r-fixed": 200,
|
1043 |
+
"CCONJ|r-orphan": 201,
|
1044 |
+
"I-ADP": 202,
|
1045 |
+
"I-ADP|Degree=Equ": 203,
|
1046 |
+
"I-ADV": 204,
|
1047 |
+
"I-ADV|AdvType=Cau": 205,
|
1048 |
+
"I-ADV|AdvType=Deg|Degree=Cmp": 206,
|
1049 |
+
"I-ADV|AdvType=Deg|Degree=Pos": 207,
|
1050 |
+
"I-ADV|AdvType=Deg|Degree=Sup": 208,
|
1051 |
+
"I-ADV|AdvType=Tim": 209,
|
1052 |
+
"I-ADV|AdvType=Tim|Aspect=Perf": 210,
|
1053 |
+
"I-ADV|AdvType=Tim|Tense=Fut": 211,
|
1054 |
+
"I-ADV|AdvType=Tim|Tense=Past": 212,
|
1055 |
+
"I-ADV|AdvType=Tim|Tense=Pres": 213,
|
1056 |
+
"I-ADV|Degree=Equ|VerbForm=Conv": 214,
|
1057 |
+
"I-ADV|Degree=Pos|VerbForm=Conv": 215,
|
1058 |
+
"I-ADV|Polarity=Neg": 216,
|
1059 |
+
"I-ADV|Polarity=Neg|VerbForm=Conv": 217,
|
1060 |
+
"I-ADV|VerbForm=Conv": 218,
|
1061 |
+
"I-AUX|Mood=Des": 219,
|
1062 |
+
"I-AUX|Mood=Nec": 220,
|
1063 |
+
"I-AUX|Mood=Pot": 221,
|
1064 |
+
"I-AUX|VerbType=Cop": 222,
|
1065 |
+
"I-AUX|Voice=Pass": 223,
|
1066 |
+
"I-CCONJ": 224,
|
1067 |
+
"I-INTJ": 225,
|
1068 |
+
"I-NOUN": 226,
|
1069 |
+
"I-NOUN|Case=Loc": 227,
|
1070 |
+
"I-NOUN|Case=Tem": 228,
|
1071 |
+
"I-NOUN|Degree=Pos": 229,
|
1072 |
+
"I-NOUN|NounType=Clf": 230,
|
1073 |
+
"I-NUM": 231,
|
1074 |
+
"I-NUM|NumType=Ord": 232,
|
1075 |
+
"I-PART": 233,
|
1076 |
+
"I-PRON|Person=1|PronType=Prs": 234,
|
1077 |
+
"I-PRON|Person=2|PronType=Prs": 235,
|
1078 |
+
"I-PRON|Person=3|PronType=Prs": 236,
|
1079 |
+
"I-PRON|PronType=Dem": 237,
|
1080 |
+
"I-PRON|PronType=Int": 238,
|
1081 |
+
"I-PRON|PronType=Prs": 239,
|
1082 |
+
"I-PRON|PronType=Prs|Reflex=Yes": 240,
|
1083 |
+
"I-PROPN": 241,
|
1084 |
+
"I-PROPN|Case=Loc|NameType=Geo": 242,
|
1085 |
+
"I-PROPN|Case=Loc|NameType=Nat": 243,
|
1086 |
+
"I-PROPN|NameType=Giv": 244,
|
1087 |
+
"I-PROPN|NameType=Prs": 245,
|
1088 |
+
"I-PROPN|NameType=Sur": 246,
|
1089 |
+
"I-PUNCT": 247,
|
1090 |
+
"I-SCONJ": 248,
|
1091 |
+
"I-SYM": 249,
|
1092 |
+
"I-VERB": 250,
|
1093 |
+
"I-VERB|Degree=Equ": 251,
|
1094 |
+
"I-VERB|Degree=Equ|VerbForm=Part": 252,
|
1095 |
+
"I-VERB|Degree=Pos": 253,
|
1096 |
+
"I-VERB|Degree=Pos|VerbForm=Part": 254,
|
1097 |
+
"I-VERB|Polarity=Neg": 255,
|
1098 |
+
"I-VERB|Polarity=Neg|VerbForm=Part": 256,
|
1099 |
+
"I-VERB|VerbForm=Part": 257,
|
1100 |
+
"INTJ": 258,
|
1101 |
+
"INTJ|l-advcl": 259,
|
1102 |
+
"INTJ|l-csubj": 260,
|
1103 |
+
"INTJ|l-discourse": 261,
|
1104 |
+
"INTJ|l-discourse:sp": 262,
|
1105 |
+
"INTJ|l-dislocated": 263,
|
1106 |
+
"INTJ|l-nsubj": 264,
|
1107 |
+
"INTJ|l-vocative": 265,
|
1108 |
+
"INTJ|r-compound:redup": 266,
|
1109 |
+
"INTJ|r-conj": 267,
|
1110 |
+
"INTJ|r-discourse:sp": 268,
|
1111 |
+
"INTJ|r-dislocated": 269,
|
1112 |
+
"INTJ|r-fixed": 270,
|
1113 |
+
"INTJ|r-obj": 271,
|
1114 |
+
"INTJ|r-parataxis": 272,
|
1115 |
+
"INTJ|root": 273,
|
1116 |
+
"NOUN": 274,
|
1117 |
+
"NOUN|Case=Loc": 275,
|
1118 |
+
"NOUN|Case=Loc|l-acl": 276,
|
1119 |
+
"NOUN|Case=Loc|l-advcl": 277,
|
1120 |
+
"NOUN|Case=Loc|l-amod": 278,
|
1121 |
+
"NOUN|Case=Loc|l-clf": 279,
|
1122 |
+
"NOUN|Case=Loc|l-compound": 280,
|
1123 |
+
"NOUN|Case=Loc|l-csubj": 281,
|
1124 |
+
"NOUN|Case=Loc|l-dislocated": 282,
|
1125 |
+
"NOUN|Case=Loc|l-nmod": 283,
|
1126 |
+
"NOUN|Case=Loc|l-nsubj": 284,
|
1127 |
+
"NOUN|Case=Loc|l-nsubj:outer": 285,
|
1128 |
+
"NOUN|Case=Loc|l-obj": 286,
|
1129 |
+
"NOUN|Case=Loc|l-obl": 287,
|
1130 |
+
"NOUN|Case=Loc|l-obl:lmod": 288,
|
1131 |
+
"NOUN|Case=Loc|l-obl:tmod": 289,
|
1132 |
+
"NOUN|Case=Loc|l-parataxis": 290,
|
1133 |
+
"NOUN|Case=Loc|r-ccomp": 291,
|
1134 |
+
"NOUN|Case=Loc|r-clf": 292,
|
1135 |
+
"NOUN|Case=Loc|r-compound:redup": 293,
|
1136 |
+
"NOUN|Case=Loc|r-conj": 294,
|
1137 |
+
"NOUN|Case=Loc|r-dislocated": 295,
|
1138 |
+
"NOUN|Case=Loc|r-flat": 296,
|
1139 |
+
"NOUN|Case=Loc|r-iobj": 297,
|
1140 |
+
"NOUN|Case=Loc|r-list": 298,
|
1141 |
+
"NOUN|Case=Loc|r-nmod": 299,
|
1142 |
+
"NOUN|Case=Loc|r-nsubj": 300,
|
1143 |
+
"NOUN|Case=Loc|r-obj": 301,
|
1144 |
+
"NOUN|Case=Loc|r-obl": 302,
|
1145 |
+
"NOUN|Case=Loc|r-obl:lmod": 303,
|
1146 |
+
"NOUN|Case=Loc|r-parataxis": 304,
|
1147 |
+
"NOUN|Case=Loc|r-xcomp": 305,
|
1148 |
+
"NOUN|Case=Loc|root": 306,
|
1149 |
+
"NOUN|Case=Tem": 307,
|
1150 |
+
"NOUN|Case=Tem|l-acl": 308,
|
1151 |
+
"NOUN|Case=Tem|l-advcl": 309,
|
1152 |
+
"NOUN|Case=Tem|l-amod": 310,
|
1153 |
+
"NOUN|Case=Tem|l-compound": 311,
|
1154 |
+
"NOUN|Case=Tem|l-csubj": 312,
|
1155 |
+
"NOUN|Case=Tem|l-nmod": 313,
|
1156 |
+
"NOUN|Case=Tem|l-nsubj": 314,
|
1157 |
+
"NOUN|Case=Tem|l-nsubj:outer": 315,
|
1158 |
+
"NOUN|Case=Tem|l-obj": 316,
|
1159 |
+
"NOUN|Case=Tem|l-obl:tmod": 317,
|
1160 |
+
"NOUN|Case=Tem|r-amod": 318,
|
1161 |
+
"NOUN|Case=Tem|r-ccomp": 319,
|
1162 |
+
"NOUN|Case=Tem|r-clf": 320,
|
1163 |
+
"NOUN|Case=Tem|r-compound:redup": 321,
|
1164 |
+
"NOUN|Case=Tem|r-conj": 322,
|
1165 |
+
"NOUN|Case=Tem|r-flat": 323,
|
1166 |
+
"NOUN|Case=Tem|r-iobj": 324,
|
1167 |
+
"NOUN|Case=Tem|r-list": 325,
|
1168 |
+
"NOUN|Case=Tem|r-nsubj": 326,
|
1169 |
+
"NOUN|Case=Tem|r-obj": 327,
|
1170 |
+
"NOUN|Case=Tem|r-obl:tmod": 328,
|
1171 |
+
"NOUN|Case=Tem|r-parataxis": 329,
|
1172 |
+
"NOUN|Case=Tem|r-xcomp": 330,
|
1173 |
+
"NOUN|Case=Tem|root": 331,
|
1174 |
+
"NOUN|Degree=Pos": 332,
|
1175 |
+
"NOUN|Degree=Pos|root": 333,
|
1176 |
+
"NOUN|NounType=Clf": 334,
|
1177 |
+
"NOUN|NounType=Clf|l-clf": 335,
|
1178 |
+
"NOUN|NounType=Clf|l-nmod": 336,
|
1179 |
+
"NOUN|NounType=Clf|l-nsubj": 337,
|
1180 |
+
"NOUN|NounType=Clf|l-obl": 338,
|
1181 |
+
"NOUN|NounType=Clf|r-ccomp": 339,
|
1182 |
+
"NOUN|NounType=Clf|r-clf": 340,
|
1183 |
+
"NOUN|NounType=Clf|r-compound:redup": 341,
|
1184 |
+
"NOUN|NounType=Clf|r-conj": 342,
|
1185 |
+
"NOUN|NounType=Clf|r-flat": 343,
|
1186 |
+
"NOUN|NounType=Clf|r-obj": 344,
|
1187 |
+
"NOUN|NounType=Clf|r-parataxis": 345,
|
1188 |
+
"NOUN|NounType=Clf|root": 346,
|
1189 |
+
"NOUN|l-acl": 347,
|
1190 |
+
"NOUN|l-advcl": 348,
|
1191 |
+
"NOUN|l-amod": 349,
|
1192 |
+
"NOUN|l-ccomp": 350,
|
1193 |
+
"NOUN|l-clf": 351,
|
1194 |
+
"NOUN|l-compound": 352,
|
1195 |
+
"NOUN|l-csubj": 353,
|
1196 |
+
"NOUN|l-csubj:outer": 354,
|
1197 |
+
"NOUN|l-dislocated": 355,
|
1198 |
+
"NOUN|l-iobj": 356,
|
1199 |
+
"NOUN|l-list": 357,
|
1200 |
+
"NOUN|l-nmod": 358,
|
1201 |
+
"NOUN|l-nsubj": 359,
|
1202 |
+
"NOUN|l-nsubj:outer": 360,
|
1203 |
+
"NOUN|l-nsubj:pass": 361,
|
1204 |
+
"NOUN|l-obj": 362,
|
1205 |
+
"NOUN|l-obl": 363,
|
1206 |
+
"NOUN|l-obl:lmod": 364,
|
1207 |
+
"NOUN|l-obl:tmod": 365,
|
1208 |
+
"NOUN|l-vocative": 366,
|
1209 |
+
"NOUN|r-acl": 367,
|
1210 |
+
"NOUN|r-advcl": 368,
|
1211 |
+
"NOUN|r-amod": 369,
|
1212 |
+
"NOUN|r-ccomp": 370,
|
1213 |
+
"NOUN|r-clf": 371,
|
1214 |
+
"NOUN|r-compound:redup": 372,
|
1215 |
+
"NOUN|r-conj": 373,
|
1216 |
+
"NOUN|r-csubj": 374,
|
1217 |
+
"NOUN|r-dislocated": 375,
|
1218 |
+
"NOUN|r-flat": 376,
|
1219 |
+
"NOUN|r-flat:foreign": 377,
|
1220 |
+
"NOUN|r-iobj": 378,
|
1221 |
+
"NOUN|r-list": 379,
|
1222 |
+
"NOUN|r-nmod": 380,
|
1223 |
+
"NOUN|r-nsubj": 381,
|
1224 |
+
"NOUN|r-obj": 382,
|
1225 |
+
"NOUN|r-obl": 383,
|
1226 |
+
"NOUN|r-obl:lmod": 384,
|
1227 |
+
"NOUN|r-parataxis": 385,
|
1228 |
+
"NOUN|r-vocative": 386,
|
1229 |
+
"NOUN|r-xcomp": 387,
|
1230 |
+
"NOUN|root": 388,
|
1231 |
+
"NUM": 389,
|
1232 |
+
"NUM|NumType=Ord": 390,
|
1233 |
+
"NUM|NumType=Ord|l-nsubj": 391,
|
1234 |
+
"NUM|NumType=Ord|l-nummod": 392,
|
1235 |
+
"NUM|NumType=Ord|l-obl": 393,
|
1236 |
+
"NUM|NumType=Ord|l-obl:lmod": 394,
|
1237 |
+
"NUM|NumType=Ord|l-obl:tmod": 395,
|
1238 |
+
"NUM|NumType=Ord|r-conj": 396,
|
1239 |
+
"NUM|NumType=Ord|r-flat": 397,
|
1240 |
+
"NUM|NumType=Ord|r-obj": 398,
|
1241 |
+
"NUM|NumType=Ord|root": 399,
|
1242 |
+
"NUM|l-acl": 400,
|
1243 |
+
"NUM|l-advcl": 401,
|
1244 |
+
"NUM|l-compound": 402,
|
1245 |
+
"NUM|l-csubj": 403,
|
1246 |
+
"NUM|l-dislocated": 404,
|
1247 |
+
"NUM|l-nsubj": 405,
|
1248 |
+
"NUM|l-nsubj:outer": 406,
|
1249 |
+
"NUM|l-nummod": 407,
|
1250 |
+
"NUM|l-obj": 408,
|
1251 |
+
"NUM|l-obl": 409,
|
1252 |
+
"NUM|l-obl:lmod": 410,
|
1253 |
+
"NUM|l-obl:tmod": 411,
|
1254 |
+
"NUM|r-ccomp": 412,
|
1255 |
+
"NUM|r-clf": 413,
|
1256 |
+
"NUM|r-compound": 414,
|
1257 |
+
"NUM|r-compound:redup": 415,
|
1258 |
+
"NUM|r-conj": 416,
|
1259 |
+
"NUM|r-flat": 417,
|
1260 |
+
"NUM|r-iobj": 418,
|
1261 |
+
"NUM|r-list": 419,
|
1262 |
+
"NUM|r-nummod": 420,
|
1263 |
+
"NUM|r-obj": 421,
|
1264 |
+
"NUM|r-obl": 422,
|
1265 |
+
"NUM|r-obl:tmod": 423,
|
1266 |
+
"NUM|r-parataxis": 424,
|
1267 |
+
"NUM|r-xcomp": 425,
|
1268 |
+
"NUM|root": 426,
|
1269 |
+
"PART": 427,
|
1270 |
+
"PART|l-acl": 428,
|
1271 |
+
"PART|l-advcl": 429,
|
1272 |
+
"PART|l-advmod": 430,
|
1273 |
+
"PART|l-amod": 431,
|
1274 |
+
"PART|l-case": 432,
|
1275 |
+
"PART|l-cc": 433,
|
1276 |
+
"PART|l-csubj": 434,
|
1277 |
+
"PART|l-csubj:outer": 435,
|
1278 |
+
"PART|l-discourse": 436,
|
1279 |
+
"PART|l-discourse:sp": 437,
|
1280 |
+
"PART|l-dislocated": 438,
|
1281 |
+
"PART|l-mark": 439,
|
1282 |
+
"PART|l-nmod": 440,
|
1283 |
+
"PART|l-nsubj": 441,
|
1284 |
+
"PART|l-nsubj:outer": 442,
|
1285 |
+
"PART|l-nsubj:pass": 443,
|
1286 |
+
"PART|l-obj": 444,
|
1287 |
+
"PART|l-obl": 445,
|
1288 |
+
"PART|l-obl:lmod": 446,
|
1289 |
+
"PART|r-advmod": 447,
|
1290 |
+
"PART|r-case": 448,
|
1291 |
+
"PART|r-ccomp": 449,
|
1292 |
+
"PART|r-clf": 450,
|
1293 |
+
"PART|r-conj": 451,
|
1294 |
+
"PART|r-discourse": 452,
|
1295 |
+
"PART|r-discourse:sp": 453,
|
1296 |
+
"PART|r-dislocated": 454,
|
1297 |
+
"PART|r-fixed": 455,
|
1298 |
+
"PART|r-flat": 456,
|
1299 |
+
"PART|r-iobj": 457,
|
1300 |
+
"PART|r-list": 458,
|
1301 |
+
"PART|r-mark": 459,
|
1302 |
+
"PART|r-nsubj": 460,
|
1303 |
+
"PART|r-obj": 461,
|
1304 |
+
"PART|r-obl": 462,
|
1305 |
+
"PART|r-parataxis": 463,
|
1306 |
+
"PART|r-xcomp": 464,
|
1307 |
+
"PART|root": 465,
|
1308 |
+
"PRON|Person=1|PronType=Prs": 466,
|
1309 |
+
"PRON|Person=1|PronType=Prs|l-acl": 467,
|
1310 |
+
"PRON|Person=1|PronType=Prs|l-advcl": 468,
|
1311 |
+
"PRON|Person=1|PronType=Prs|l-det": 469,
|
1312 |
+
"PRON|Person=1|PronType=Prs|l-iobj": 470,
|
1313 |
+
"PRON|Person=1|PronType=Prs|l-nsubj": 471,
|
1314 |
+
"PRON|Person=1|PronType=Prs|l-nsubj:outer": 472,
|
1315 |
+
"PRON|Person=1|PronType=Prs|l-obj": 473,
|
1316 |
+
"PRON|Person=1|PronType=Prs|l-obl": 474,
|
1317 |
+
"PRON|Person=1|PronType=Prs|l-vocative": 475,
|
1318 |
+
"PRON|Person=1|PronType=Prs|r-ccomp": 476,
|
1319 |
+
"PRON|Person=1|PronType=Prs|r-conj": 477,
|
1320 |
+
"PRON|Person=1|PronType=Prs|r-iobj": 478,
|
1321 |
+
"PRON|Person=1|PronType=Prs|r-nsubj": 479,
|
1322 |
+
"PRON|Person=1|PronType=Prs|r-obj": 480,
|
1323 |
+
"PRON|Person=1|PronType=Prs|r-obl": 481,
|
1324 |
+
"PRON|Person=1|PronType=Prs|r-obl:lmod": 482,
|
1325 |
+
"PRON|Person=1|PronType=Prs|root": 483,
|
1326 |
+
"PRON|Person=2|PronType=Prs": 484,
|
1327 |
+
"PRON|Person=2|PronType=Prs|l-advcl": 485,
|
1328 |
+
"PRON|Person=2|PronType=Prs|l-amod": 486,
|
1329 |
+
"PRON|Person=2|PronType=Prs|l-det": 487,
|
1330 |
+
"PRON|Person=2|PronType=Prs|l-nsubj": 488,
|
1331 |
+
"PRON|Person=2|PronType=Prs|l-nsubj:outer": 489,
|
1332 |
+
"PRON|Person=2|PronType=Prs|l-obj": 490,
|
1333 |
+
"PRON|Person=2|PronType=Prs|l-obl": 491,
|
1334 |
+
"PRON|Person=2|PronType=Prs|l-vocative": 492,
|
1335 |
+
"PRON|Person=2|PronType=Prs|r-conj": 493,
|
1336 |
+
"PRON|Person=2|PronType=Prs|r-flat": 494,
|
1337 |
+
"PRON|Person=2|PronType=Prs|r-iobj": 495,
|
1338 |
+
"PRON|Person=2|PronType=Prs|r-obj": 496,
|
1339 |
+
"PRON|Person=2|PronType=Prs|r-obl": 497,
|
1340 |
+
"PRON|Person=2|PronType=Prs|root": 498,
|
1341 |
+
"PRON|Person=3|PronType=Prs": 499,
|
1342 |
+
"PRON|Person=3|PronType=Prs|l-advcl": 500,
|
1343 |
+
"PRON|Person=3|PronType=Prs|l-amod": 501,
|
1344 |
+
"PRON|Person=3|PronType=Prs|l-det": 502,
|
1345 |
+
"PRON|Person=3|PronType=Prs|l-dislocated": 503,
|
1346 |
+
"PRON|Person=3|PronType=Prs|l-expl": 504,
|
1347 |
+
"PRON|Person=3|PronType=Prs|l-iobj": 505,
|
1348 |
+
"PRON|Person=3|PronType=Prs|l-nsubj": 506,
|
1349 |
+
"PRON|Person=3|PronType=Prs|l-nsubj:outer": 507,
|
1350 |
+
"PRON|Person=3|PronType=Prs|l-nsubj:pass": 508,
|
1351 |
+
"PRON|Person=3|PronType=Prs|l-obj": 509,
|
1352 |
+
"PRON|Person=3|PronType=Prs|l-obl": 510,
|
1353 |
+
"PRON|Person=3|PronType=Prs|r-ccomp": 511,
|
1354 |
+
"PRON|Person=3|PronType=Prs|r-conj": 512,
|
1355 |
+
"PRON|Person=3|PronType=Prs|r-expl": 513,
|
1356 |
+
"PRON|Person=3|PronType=Prs|r-iobj": 514,
|
1357 |
+
"PRON|Person=3|PronType=Prs|r-nsubj": 515,
|
1358 |
+
"PRON|Person=3|PronType=Prs|r-obj": 516,
|
1359 |
+
"PRON|Person=3|PronType=Prs|r-obl": 517,
|
1360 |
+
"PRON|Person=3|PronType=Prs|root": 518,
|
1361 |
+
"PRON|PronType=Dem": 519,
|
1362 |
+
"PRON|PronType=Dem|l-acl": 520,
|
1363 |
+
"PRON|PronType=Dem|l-advcl": 521,
|
1364 |
+
"PRON|PronType=Dem|l-amod": 522,
|
1365 |
+
"PRON|PronType=Dem|l-compound": 523,
|
1366 |
+
"PRON|PronType=Dem|l-det": 524,
|
1367 |
+
"PRON|PronType=Dem|l-dislocated": 525,
|
1368 |
+
"PRON|PronType=Dem|l-expl": 526,
|
1369 |
+
"PRON|PronType=Dem|l-nsubj": 527,
|
1370 |
+
"PRON|PronType=Dem|l-nsubj:outer": 528,
|
1371 |
+
"PRON|PronType=Dem|l-obj": 529,
|
1372 |
+
"PRON|PronType=Dem|l-obl": 530,
|
1373 |
+
"PRON|PronType=Dem|l-obl:lmod": 531,
|
1374 |
+
"PRON|PronType=Dem|r-conj": 532,
|
1375 |
+
"PRON|PronType=Dem|r-det": 533,
|
1376 |
+
"PRON|PronType=Dem|r-expl": 534,
|
1377 |
+
"PRON|PronType=Dem|r-flat": 535,
|
1378 |
+
"PRON|PronType=Dem|r-iobj": 536,
|
1379 |
+
"PRON|PronType=Dem|r-obj": 537,
|
1380 |
+
"PRON|PronType=Dem|r-obl": 538,
|
1381 |
+
"PRON|PronType=Dem|r-obl:lmod": 539,
|
1382 |
+
"PRON|PronType=Dem|root": 540,
|
1383 |
+
"PRON|PronType=Int": 541,
|
1384 |
+
"PRON|PronType=Int|l-advcl": 542,
|
1385 |
+
"PRON|PronType=Int|l-amod": 543,
|
1386 |
+
"PRON|PronType=Int|l-det": 544,
|
1387 |
+
"PRON|PronType=Int|l-dislocated": 545,
|
1388 |
+
"PRON|PronType=Int|l-nsubj": 546,
|
1389 |
+
"PRON|PronType=Int|l-nsubj:outer": 547,
|
1390 |
+
"PRON|PronType=Int|l-obj": 548,
|
1391 |
+
"PRON|PronType=Int|l-obl": 549,
|
1392 |
+
"PRON|PronType=Int|l-vocative": 550,
|
1393 |
+
"PRON|PronType=Int|r-ccomp": 551,
|
1394 |
+
"PRON|PronType=Int|r-conj": 552,
|
1395 |
+
"PRON|PronType=Int|r-flat": 553,
|
1396 |
+
"PRON|PronType=Int|r-obj": 554,
|
1397 |
+
"PRON|PronType=Int|r-parataxis": 555,
|
1398 |
+
"PRON|PronType=Int|r-xcomp": 556,
|
1399 |
+
"PRON|PronType=Int|root": 557,
|
1400 |
+
"PRON|PronType=Prs": 558,
|
1401 |
+
"PRON|PronType=Prs|Reflex=Yes": 559,
|
1402 |
+
"PRON|PronType=Prs|Reflex=Yes|l-acl": 560,
|
1403 |
+
"PRON|PronType=Prs|Reflex=Yes|l-det": 561,
|
1404 |
+
"PRON|PronType=Prs|Reflex=Yes|l-nsubj": 562,
|
1405 |
+
"PRON|PronType=Prs|Reflex=Yes|l-obj": 563,
|
1406 |
+
"PRON|PronType=Prs|Reflex=Yes|l-obl": 564,
|
1407 |
+
"PRON|PronType=Prs|Reflex=Yes|r-dislocated": 565,
|
1408 |
+
"PRON|PronType=Prs|Reflex=Yes|r-obj": 566,
|
1409 |
+
"PRON|PronType=Prs|Reflex=Yes|r-obl": 567,
|
1410 |
+
"PRON|PronType=Prs|Reflex=Yes|root": 568,
|
1411 |
+
"PRON|PronType=Prs|l-det": 569,
|
1412 |
+
"PRON|PronType=Prs|l-nsubj": 570,
|
1413 |
+
"PRON|PronType=Prs|l-nsubj:outer": 571,
|
1414 |
+
"PRON|PronType=Prs|l-obj": 572,
|
1415 |
+
"PRON|PronType=Prs|r-conj": 573,
|
1416 |
+
"PRON|PronType=Prs|r-iobj": 574,
|
1417 |
+
"PRON|PronType=Prs|r-obj": 575,
|
1418 |
+
"PROPN": 576,
|
1419 |
+
"PROPN|Case=Loc|NameType=Geo": 577,
|
1420 |
+
"PROPN|Case=Loc|NameType=Geo|l-acl": 578,
|
1421 |
+
"PROPN|Case=Loc|NameType=Geo|l-advcl": 579,
|
1422 |
+
"PROPN|Case=Loc|NameType=Geo|l-amod": 580,
|
1423 |
+
"PROPN|Case=Loc|NameType=Geo|l-compound": 581,
|
1424 |
+
"PROPN|Case=Loc|NameType=Geo|l-csubj": 582,
|
1425 |
+
"PROPN|Case=Loc|NameType=Geo|l-dislocated": 583,
|
1426 |
+
"PROPN|Case=Loc|NameType=Geo|l-nmod": 584,
|
1427 |
+
"PROPN|Case=Loc|NameType=Geo|l-nsubj": 585,
|
1428 |
+
"PROPN|Case=Loc|NameType=Geo|l-nsubj:outer": 586,
|
1429 |
+
"PROPN|Case=Loc|NameType=Geo|l-obl": 587,
|
1430 |
+
"PROPN|Case=Loc|NameType=Geo|l-obl:lmod": 588,
|
1431 |
+
"PROPN|Case=Loc|NameType=Geo|r-conj": 589,
|
1432 |
+
"PROPN|Case=Loc|NameType=Geo|r-flat": 590,
|
1433 |
+
"PROPN|Case=Loc|NameType=Geo|r-iobj": 591,
|
1434 |
+
"PROPN|Case=Loc|NameType=Geo|r-obj": 592,
|
1435 |
+
"PROPN|Case=Loc|NameType=Geo|r-obl": 593,
|
1436 |
+
"PROPN|Case=Loc|NameType=Geo|r-obl:lmod": 594,
|
1437 |
+
"PROPN|Case=Loc|NameType=Geo|r-parataxis": 595,
|
1438 |
+
"PROPN|Case=Loc|NameType=Geo|r-xcomp": 596,
|
1439 |
+
"PROPN|Case=Loc|NameType=Geo|root": 597,
|
1440 |
+
"PROPN|Case=Loc|NameType=Nat": 598,
|
1441 |
+
"PROPN|Case=Loc|NameType=Nat|l-acl": 599,
|
1442 |
+
"PROPN|Case=Loc|NameType=Nat|l-advcl": 600,
|
1443 |
+
"PROPN|Case=Loc|NameType=Nat|l-amod": 601,
|
1444 |
+
"PROPN|Case=Loc|NameType=Nat|l-clf": 602,
|
1445 |
+
"PROPN|Case=Loc|NameType=Nat|l-compound": 603,
|
1446 |
+
"PROPN|Case=Loc|NameType=Nat|l-nmod": 604,
|
1447 |
+
"PROPN|Case=Loc|NameType=Nat|l-nsubj": 605,
|
1448 |
+
"PROPN|Case=Loc|NameType=Nat|l-nsubj:outer": 606,
|
1449 |
+
"PROPN|Case=Loc|NameType=Nat|l-nsubj:pass": 607,
|
1450 |
+
"PROPN|Case=Loc|NameType=Nat|l-obj": 608,
|
1451 |
+
"PROPN|Case=Loc|NameType=Nat|l-obl": 609,
|
1452 |
+
"PROPN|Case=Loc|NameType=Nat|l-obl:lmod": 610,
|
1453 |
+
"PROPN|Case=Loc|NameType=Nat|r-ccomp": 611,
|
1454 |
+
"PROPN|Case=Loc|NameType=Nat|r-conj": 612,
|
1455 |
+
"PROPN|Case=Loc|NameType=Nat|r-flat": 613,
|
1456 |
+
"PROPN|Case=Loc|NameType=Nat|r-iobj": 614,
|
1457 |
+
"PROPN|Case=Loc|NameType=Nat|r-nmod": 615,
|
1458 |
+
"PROPN|Case=Loc|NameType=Nat|r-obj": 616,
|
1459 |
+
"PROPN|Case=Loc|NameType=Nat|r-obl": 617,
|
1460 |
+
"PROPN|Case=Loc|NameType=Nat|r-obl:lmod": 618,
|
1461 |
+
"PROPN|Case=Loc|NameType=Nat|r-parataxis": 619,
|
1462 |
+
"PROPN|Case=Loc|NameType=Nat|r-xcomp": 620,
|
1463 |
+
"PROPN|Case=Loc|NameType=Nat|root": 621,
|
1464 |
+
"PROPN|NameType=Giv": 622,
|
1465 |
+
"PROPN|NameType=Giv|l-acl": 623,
|
1466 |
+
"PROPN|NameType=Giv|l-advcl": 624,
|
1467 |
+
"PROPN|NameType=Giv|l-amod": 625,
|
1468 |
+
"PROPN|NameType=Giv|l-compound": 626,
|
1469 |
+
"PROPN|NameType=Giv|l-dislocated": 627,
|
1470 |
+
"PROPN|NameType=Giv|l-nmod": 628,
|
1471 |
+
"PROPN|NameType=Giv|l-nsubj": 629,
|
1472 |
+
"PROPN|NameType=Giv|l-nsubj:outer": 630,
|
1473 |
+
"PROPN|NameType=Giv|l-nsubj:pass": 631,
|
1474 |
+
"PROPN|NameType=Giv|l-obj": 632,
|
1475 |
+
"PROPN|NameType=Giv|l-obl": 633,
|
1476 |
+
"PROPN|NameType=Giv|l-obl:lmod": 634,
|
1477 |
+
"PROPN|NameType=Giv|l-parataxis": 635,
|
1478 |
+
"PROPN|NameType=Giv|l-vocative": 636,
|
1479 |
+
"PROPN|NameType=Giv|r-ccomp": 637,
|
1480 |
+
"PROPN|NameType=Giv|r-conj": 638,
|
1481 |
+
"PROPN|NameType=Giv|r-dislocated": 639,
|
1482 |
+
"PROPN|NameType=Giv|r-flat": 640,
|
1483 |
+
"PROPN|NameType=Giv|r-iobj": 641,
|
1484 |
+
"PROPN|NameType=Giv|r-list": 642,
|
1485 |
+
"PROPN|NameType=Giv|r-nmod": 643,
|
1486 |
+
"PROPN|NameType=Giv|r-obj": 644,
|
1487 |
+
"PROPN|NameType=Giv|r-obl": 645,
|
1488 |
+
"PROPN|NameType=Giv|r-obl:lmod": 646,
|
1489 |
+
"PROPN|NameType=Giv|r-parataxis": 647,
|
1490 |
+
"PROPN|NameType=Giv|r-xcomp": 648,
|
1491 |
+
"PROPN|NameType=Giv|root": 649,
|
1492 |
+
"PROPN|NameType=Prs": 650,
|
1493 |
+
"PROPN|NameType=Prs|l-acl": 651,
|
1494 |
+
"PROPN|NameType=Prs|l-advcl": 652,
|
1495 |
+
"PROPN|NameType=Prs|l-amod": 653,
|
1496 |
+
"PROPN|NameType=Prs|l-compound": 654,
|
1497 |
+
"PROPN|NameType=Prs|l-dislocated": 655,
|
1498 |
+
"PROPN|NameType=Prs|l-nmod": 656,
|
1499 |
+
"PROPN|NameType=Prs|l-nsubj": 657,
|
1500 |
+
"PROPN|NameType=Prs|l-nsubj:outer": 658,
|
1501 |
+
"PROPN|NameType=Prs|l-obj": 659,
|
1502 |
+
"PROPN|NameType=Prs|l-obl": 660,
|
1503 |
+
"PROPN|NameType=Prs|r-conj": 661,
|
1504 |
+
"PROPN|NameType=Prs|r-dislocated": 662,
|
1505 |
+
"PROPN|NameType=Prs|r-flat": 663,
|
1506 |
+
"PROPN|NameType=Prs|r-iobj": 664,
|
1507 |
+
"PROPN|NameType=Prs|r-obj": 665,
|
1508 |
+
"PROPN|NameType=Prs|r-obl": 666,
|
1509 |
+
"PROPN|NameType=Prs|r-parataxis": 667,
|
1510 |
+
"PROPN|NameType=Prs|root": 668,
|
1511 |
+
"PROPN|NameType=Sur": 669,
|
1512 |
+
"PROPN|NameType=Sur|l-acl": 670,
|
1513 |
+
"PROPN|NameType=Sur|l-advcl": 671,
|
1514 |
+
"PROPN|NameType=Sur|l-amod": 672,
|
1515 |
+
"PROPN|NameType=Sur|l-compound": 673,
|
1516 |
+
"PROPN|NameType=Sur|l-csubj": 674,
|
1517 |
+
"PROPN|NameType=Sur|l-dislocated": 675,
|
1518 |
+
"PROPN|NameType=Sur|l-nmod": 676,
|
1519 |
+
"PROPN|NameType=Sur|l-nsubj": 677,
|
1520 |
+
"PROPN|NameType=Sur|l-nsubj:outer": 678,
|
1521 |
+
"PROPN|NameType=Sur|l-nsubj:pass": 679,
|
1522 |
+
"PROPN|NameType=Sur|l-obl": 680,
|
1523 |
+
"PROPN|NameType=Sur|l-obl:lmod": 681,
|
1524 |
+
"PROPN|NameType=Sur|l-vocative": 682,
|
1525 |
+
"PROPN|NameType=Sur|r-ccomp": 683,
|
1526 |
+
"PROPN|NameType=Sur|r-conj": 684,
|
1527 |
+
"PROPN|NameType=Sur|r-dislocated": 685,
|
1528 |
+
"PROPN|NameType=Sur|r-flat": 686,
|
1529 |
+
"PROPN|NameType=Sur|r-iobj": 687,
|
1530 |
+
"PROPN|NameType=Sur|r-list": 688,
|
1531 |
+
"PROPN|NameType=Sur|r-nmod": 689,
|
1532 |
+
"PROPN|NameType=Sur|r-nsubj": 690,
|
1533 |
+
"PROPN|NameType=Sur|r-obj": 691,
|
1534 |
+
"PROPN|NameType=Sur|r-obl": 692,
|
1535 |
+
"PROPN|NameType=Sur|r-obl:lmod": 693,
|
1536 |
+
"PROPN|NameType=Sur|r-parataxis": 694,
|
1537 |
+
"PROPN|NameType=Sur|r-xcomp": 695,
|
1538 |
+
"PROPN|NameType=Sur|root": 696,
|
1539 |
+
"PROPN|l-nmod": 697,
|
1540 |
+
"PUNCT": 698,
|
1541 |
+
"PUNCT|root": 699,
|
1542 |
+
"SCONJ": 700,
|
1543 |
+
"SCONJ|l-case": 701,
|
1544 |
+
"SCONJ|l-cc": 702,
|
1545 |
+
"SCONJ|l-mark": 703,
|
1546 |
+
"SCONJ|l-nsubj": 704,
|
1547 |
+
"SCONJ|l-obl": 705,
|
1548 |
+
"SCONJ|r-case": 706,
|
1549 |
+
"SCONJ|r-iobj": 707,
|
1550 |
+
"SCONJ|r-mark": 708,
|
1551 |
+
"SCONJ|r-nsubj": 709,
|
1552 |
+
"SCONJ|r-nsubj:pass": 710,
|
1553 |
+
"SCONJ|r-obj": 711,
|
1554 |
+
"SCONJ|root": 712,
|
1555 |
+
"SYM": 713,
|
1556 |
+
"SYM|l-nmod": 714,
|
1557 |
+
"SYM|l-nsubj": 715,
|
1558 |
+
"SYM|r-conj": 716,
|
1559 |
+
"SYM|r-nmod": 717,
|
1560 |
+
"SYM|r-xcomp": 718,
|
1561 |
+
"SYM|root": 719,
|
1562 |
+
"VERB": 720,
|
1563 |
+
"VERB|Degree=Equ": 721,
|
1564 |
+
"VERB|Degree=Equ|VerbForm=Part": 722,
|
1565 |
+
"VERB|Degree=Equ|VerbForm=Part|l-amod": 723,
|
1566 |
+
"VERB|Degree=Equ|l-acl": 724,
|
1567 |
+
"VERB|Degree=Equ|l-advcl": 725,
|
1568 |
+
"VERB|Degree=Equ|l-ccomp": 726,
|
1569 |
+
"VERB|Degree=Equ|l-csubj": 727,
|
1570 |
+
"VERB|Degree=Equ|l-nsubj": 728,
|
1571 |
+
"VERB|Degree=Equ|l-obj": 729,
|
1572 |
+
"VERB|Degree=Equ|r-ccomp": 730,
|
1573 |
+
"VERB|Degree=Equ|r-compound:redup": 731,
|
1574 |
+
"VERB|Degree=Equ|r-conj": 732,
|
1575 |
+
"VERB|Degree=Equ|r-obj": 733,
|
1576 |
+
"VERB|Degree=Equ|r-parataxis": 734,
|
1577 |
+
"VERB|Degree=Equ|r-xcomp": 735,
|
1578 |
+
"VERB|Degree=Equ|root": 736,
|
1579 |
+
"VERB|Degree=Pos": 737,
|
1580 |
+
"VERB|Degree=Pos|VerbForm=Part": 738,
|
1581 |
+
"VERB|Degree=Pos|VerbForm=Part|l-amod": 739,
|
1582 |
+
"VERB|Degree=Pos|VerbForm=Part|r-amod": 740,
|
1583 |
+
"VERB|Degree=Pos|l-acl": 741,
|
1584 |
+
"VERB|Degree=Pos|l-advcl": 742,
|
1585 |
+
"VERB|Degree=Pos|l-ccomp": 743,
|
1586 |
+
"VERB|Degree=Pos|l-csubj": 744,
|
1587 |
+
"VERB|Degree=Pos|l-csubj:outer": 745,
|
1588 |
+
"VERB|Degree=Pos|l-dislocated": 746,
|
1589 |
+
"VERB|Degree=Pos|l-nsubj": 747,
|
1590 |
+
"VERB|Degree=Pos|l-nsubj:outer": 748,
|
1591 |
+
"VERB|Degree=Pos|l-obj": 749,
|
1592 |
+
"VERB|Degree=Pos|l-obl": 750,
|
1593 |
+
"VERB|Degree=Pos|l-vocative": 751,
|
1594 |
+
"VERB|Degree=Pos|r-advcl": 752,
|
1595 |
+
"VERB|Degree=Pos|r-ccomp": 753,
|
1596 |
+
"VERB|Degree=Pos|r-compound:redup": 754,
|
1597 |
+
"VERB|Degree=Pos|r-conj": 755,
|
1598 |
+
"VERB|Degree=Pos|r-dislocated": 756,
|
1599 |
+
"VERB|Degree=Pos|r-fixed": 757,
|
1600 |
+
"VERB|Degree=Pos|r-flat:vv": 758,
|
1601 |
+
"VERB|Degree=Pos|r-iobj": 759,
|
1602 |
+
"VERB|Degree=Pos|r-obj": 760,
|
1603 |
+
"VERB|Degree=Pos|r-obl": 761,
|
1604 |
+
"VERB|Degree=Pos|r-parataxis": 762,
|
1605 |
+
"VERB|Degree=Pos|r-xcomp": 763,
|
1606 |
+
"VERB|Degree=Pos|root": 764,
|
1607 |
+
"VERB|Polarity=Neg": 765,
|
1608 |
+
"VERB|Polarity=Neg|VerbForm=Part": 766,
|
1609 |
+
"VERB|Polarity=Neg|VerbForm=Part|l-amod": 767,
|
1610 |
+
"VERB|Polarity=Neg|l-acl": 768,
|
1611 |
+
"VERB|Polarity=Neg|l-advcl": 769,
|
1612 |
+
"VERB|Polarity=Neg|l-ccomp": 770,
|
1613 |
+
"VERB|Polarity=Neg|l-csubj": 771,
|
1614 |
+
"VERB|Polarity=Neg|l-csubj:outer": 772,
|
1615 |
+
"VERB|Polarity=Neg|l-nsubj": 773,
|
1616 |
+
"VERB|Polarity=Neg|l-obl": 774,
|
1617 |
+
"VERB|Polarity=Neg|r-advcl": 775,
|
1618 |
+
"VERB|Polarity=Neg|r-ccomp": 776,
|
1619 |
+
"VERB|Polarity=Neg|r-conj": 777,
|
1620 |
+
"VERB|Polarity=Neg|r-flat:vv": 778,
|
1621 |
+
"VERB|Polarity=Neg|r-obj": 779,
|
1622 |
+
"VERB|Polarity=Neg|r-obl": 780,
|
1623 |
+
"VERB|Polarity=Neg|r-parataxis": 781,
|
1624 |
+
"VERB|Polarity=Neg|r-xcomp": 782,
|
1625 |
+
"VERB|Polarity=Neg|root": 783,
|
1626 |
+
"VERB|VerbForm=Part": 784,
|
1627 |
+
"VERB|VerbForm=Part|l-amod": 785,
|
1628 |
+
"VERB|VerbForm=Part|r-amod": 786,
|
1629 |
+
"VERB|l-acl": 787,
|
1630 |
+
"VERB|l-advcl": 788,
|
1631 |
+
"VERB|l-ccomp": 789,
|
1632 |
+
"VERB|l-csubj": 790,
|
1633 |
+
"VERB|l-csubj:outer": 791,
|
1634 |
+
"VERB|l-csubj:pass": 792,
|
1635 |
+
"VERB|l-dislocated": 793,
|
1636 |
+
"VERB|l-nsubj": 794,
|
1637 |
+
"VERB|l-nsubj:outer": 795,
|
1638 |
+
"VERB|l-obj": 796,
|
1639 |
+
"VERB|l-obl": 797,
|
1640 |
+
"VERB|l-obl:lmod": 798,
|
1641 |
+
"VERB|l-parataxis": 799,
|
1642 |
+
"VERB|r-acl": 800,
|
1643 |
+
"VERB|r-advcl": 801,
|
1644 |
+
"VERB|r-ccomp": 802,
|
1645 |
+
"VERB|r-compound:redup": 803,
|
1646 |
+
"VERB|r-conj": 804,
|
1647 |
+
"VERB|r-dislocated": 805,
|
1648 |
+
"VERB|r-fixed": 806,
|
1649 |
+
"VERB|r-flat:vv": 807,
|
1650 |
+
"VERB|r-iobj": 808,
|
1651 |
+
"VERB|r-list": 809,
|
1652 |
+
"VERB|r-obj": 810,
|
1653 |
+
"VERB|r-obl": 811,
|
1654 |
+
"VERB|r-obl:lmod": 812,
|
1655 |
+
"VERB|r-parataxis": 813,
|
1656 |
+
"VERB|r-vocative": 814,
|
1657 |
+
"VERB|r-xcomp": 815,
|
1658 |
+
"VERB|root": 816
|
1659 |
+
},
|
1660 |
+
"max_position_embeddings": 131072,
|
1661 |
+
"max_window_layers": 28,
|
1662 |
+
"model_type": "qwen2",
|
1663 |
+
"num_attention_heads": 12,
|
1664 |
+
"num_hidden_layers": 28,
|
1665 |
+
"num_key_value_heads": 2,
|
1666 |
+
"rms_norm_eps": 1e-06,
|
1667 |
+
"rope_theta": 1000000.0,
|
1668 |
+
"sliding_window": 131072,
|
1669 |
+
"tie_word_embeddings": true,
|
1670 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
1671 |
+
"torch_dtype": "float32",
|
1672 |
+
"transformers_version": "4.42.4",
|
1673 |
+
"use_cache": false,
|
1674 |
+
"use_sliding_window": false,
|
1675 |
+
"vocab_size": 151936
|
1676 |
+
}
|
maker.py
ADDED
@@ -0,0 +1,108 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
#! /usr/bin/python3
|
2 |
+
src="KoichiYasuoka/Xunzi-Qwen2-1.5B-upos"
|
3 |
+
tgt="KoichiYasuoka/Xunzi-Qwen2-1.5B-ud-causal"
|
4 |
+
url="https://github.com/UniversalDependencies/UD_Classical_Chinese-Kyoto"
|
5 |
+
import os
|
6 |
+
d=os.path.basename(url)
|
7 |
+
os.system("test -d "+d+" || git clone --depth=1 "+url)
|
8 |
+
os.system("for F in train dev test ; do cp "+d+"/*-$F.conllu $F.conllu ; done")
|
9 |
+
class UDCausalDataset(object):
|
10 |
+
def __init__(self,conllu,tokenizer,embeddings=None):
|
11 |
+
self.conllu=open(conllu,"r",encoding="utf-8")
|
12 |
+
self.tokenizer=tokenizer
|
13 |
+
self.embeddings=embeddings
|
14 |
+
self.max_tokens=3
|
15 |
+
self.seeks=[(0,0)]
|
16 |
+
label=set(["SYM"])
|
17 |
+
dep=set()
|
18 |
+
s=self.conllu.readline()
|
19 |
+
while s!="":
|
20 |
+
if s=="\n":
|
21 |
+
self.seeks.append((self.conllu.tell(),0))
|
22 |
+
else:
|
23 |
+
w=s.split("\t")
|
24 |
+
if len(w)==10:
|
25 |
+
if w[0].isdecimal():
|
26 |
+
p=w[3] if w[5]=="_" else w[3]+"|"+w[5]
|
27 |
+
label.add(p)
|
28 |
+
dep.add(p+("|" if w[6]=="0" else "|l-" if int(w[0])<int(w[6]) else "|r-")+w[7])
|
29 |
+
self.seeks.append((self.seeks[-1][0],int(w[0])))
|
30 |
+
self.max_tokens=max(self.max_tokens,int(w[0])*2+1)
|
31 |
+
s=self.conllu.readline()
|
32 |
+
lid={}
|
33 |
+
for i,l in enumerate(sorted(label)):
|
34 |
+
lid[l],lid["B-"+l],lid["I-"+l]=i*3,i*3+1,i*3+2
|
35 |
+
for i,d in enumerate(sorted(dep),len(lid)):
|
36 |
+
lid[d]=i
|
37 |
+
self.label2id=lid
|
38 |
+
def __call__(*args):
|
39 |
+
lid={l:i for i,l in enumerate(sorted(set(sum([list(t.label2id) for t in args],[]))))}
|
40 |
+
for t in args:
|
41 |
+
t.label2id=lid
|
42 |
+
return lid
|
43 |
+
def __del__(self):
|
44 |
+
self.conllu.close()
|
45 |
+
__len__=lambda self:len(self.seeks)-1
|
46 |
+
def __getitem__(self,i):
|
47 |
+
s,t=self.seeks[i]
|
48 |
+
self.conllu.seek(s)
|
49 |
+
form,upos,deps,w=[],[],[],[""]
|
50 |
+
while w[0]!="\n":
|
51 |
+
w=self.conllu.readline().split("\t")
|
52 |
+
if len(w)==10:
|
53 |
+
form.append(w[1])
|
54 |
+
if w[0].isdecimal():
|
55 |
+
upos.append(w[3] if w[5]=="_" else w[3]+"|"+w[5])
|
56 |
+
deps.append((int(w[6]),w[7]))
|
57 |
+
v=self.tokenizer(form,add_special_tokens=False)
|
58 |
+
if t==0:
|
59 |
+
i,u=[],[]
|
60 |
+
for j,(x,y) in enumerate(zip(v["input_ids"],upos)):
|
61 |
+
if x!=[]:
|
62 |
+
i+=x
|
63 |
+
u+=[y] if len(x)==1 else ["B-"+y]+["I-"+y]*(len(x)-1)
|
64 |
+
emb=self.embeddings
|
65 |
+
pad=self.tokenizer.pad_token_id
|
66 |
+
else:
|
67 |
+
import torch
|
68 |
+
m=[]
|
69 |
+
for x in v["input_ids"]:
|
70 |
+
if x==[]:
|
71 |
+
m.append(self.embeddings[self.tokenizer.unk_token_id,:])
|
72 |
+
else:
|
73 |
+
m.append(self.embeddings[x,:].sum(axis=0))
|
74 |
+
m.append(self.embeddings[self.tokenizer.sep_token_id,:])
|
75 |
+
m.append(self.embeddings[self.tokenizer.pad_token_id,:])
|
76 |
+
emb=torch.stack(m)
|
77 |
+
i,u=list(range(len(upos)+1)),upos+["SYM"]
|
78 |
+
i.append(t-1)
|
79 |
+
k,d=deps[t-1]
|
80 |
+
u.append(upos[t-1]+"|"+d if k==0 else upos[t-1])
|
81 |
+
for j in range(t,len(upos)):
|
82 |
+
i.append(j)
|
83 |
+
a,b=deps[j]
|
84 |
+
u.append(upos[j]+"|r-"+b if a==t else upos[t-1]+"|l-"+d if j+1==k else upos[j])
|
85 |
+
pad=-1
|
86 |
+
j=self.max_tokens-len(i)
|
87 |
+
if j>0:
|
88 |
+
ids=i+[pad]*j
|
89 |
+
upos=u+["SYM"]*j
|
90 |
+
else:
|
91 |
+
ids=i[0:self.max_tokens]
|
92 |
+
upos=u[0:self.max_tokens]
|
93 |
+
return {"inputs_embeds":emb[ids,:],"labels":[self.label2id[p] for p in upos]}
|
94 |
+
from transformers import AutoTokenizer,AutoConfig,Qwen2ForTokenClassification,DefaultDataCollator,TrainingArguments,Trainer
|
95 |
+
tkz=AutoTokenizer.from_pretrained(src,cls_token="<|im_start|>",sep_token="<|im_end|>",mask_token="<unk>")
|
96 |
+
trainDS=UDCausalDataset("train.conllu",tkz)
|
97 |
+
devDS=UDCausalDataset("dev.conllu",tkz)
|
98 |
+
testDS=UDCausalDataset("test.conllu",tkz)
|
99 |
+
lid=trainDS(devDS,testDS)
|
100 |
+
cfg=AutoConfig.from_pretrained(src,num_labels=len(lid),label2id=lid,id2label={i:l for l,i in lid.items()},ignore_mismatched_sizes=True)
|
101 |
+
mdl=Qwen2ForTokenClassification.from_pretrained(src,config=cfg,ignore_mismatched_sizes=True)
|
102 |
+
trainDS.embeddings=mdl.get_input_embeddings().weight
|
103 |
+
trainDS.max_tokens=min(trainDS.max_tokens,cfg.max_position_embeddings)
|
104 |
+
arg=TrainingArguments(num_train_epochs=3,per_device_train_batch_size=12,dataloader_pin_memory=False,output_dir=tgt,overwrite_output_dir=True,save_total_limit=2,learning_rate=5e-05,warmup_ratio=0.1,save_safetensors=False)
|
105 |
+
trn=Trainer(args=arg,data_collator=DefaultDataCollator(),model=mdl,train_dataset=trainDS)
|
106 |
+
trn.train()
|
107 |
+
trn.save_model(tgt)
|
108 |
+
tkz.save_pretrained(tgt)
|
merges.txt
ADDED
The diff for this file is too large to render.
See raw diff
|
|
pytorch_model-00001-of-00002.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:1a9a8fe436930b4571843166b905238634592c070ab319d332dcdc35eba281bc
|
3 |
+
size 4996733492
|
pytorch_model-00002-of-00002.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:8cf1a3220364c5045d865cf6ed5521751cbb1fd0f0a1db1424585be7df3f5220
|
3 |
+
size 1183266918
|
pytorch_model.bin.index.json
ADDED
@@ -0,0 +1,347 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"metadata": {
|
3 |
+
"total_size": 6179880132
|
4 |
+
},
|
5 |
+
"weight_map": {
|
6 |
+
"model.embed_tokens.weight": "pytorch_model-00001-of-00002.bin",
|
7 |
+
"model.layers.0.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
8 |
+
"model.layers.0.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
9 |
+
"model.layers.0.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
10 |
+
"model.layers.0.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
11 |
+
"model.layers.0.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
12 |
+
"model.layers.0.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
13 |
+
"model.layers.0.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
14 |
+
"model.layers.0.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
15 |
+
"model.layers.0.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
16 |
+
"model.layers.0.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
17 |
+
"model.layers.0.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
18 |
+
"model.layers.0.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
19 |
+
"model.layers.1.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
20 |
+
"model.layers.1.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
21 |
+
"model.layers.1.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
22 |
+
"model.layers.1.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
23 |
+
"model.layers.1.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
24 |
+
"model.layers.1.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
25 |
+
"model.layers.1.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
26 |
+
"model.layers.1.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
27 |
+
"model.layers.1.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
28 |
+
"model.layers.1.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
29 |
+
"model.layers.1.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
30 |
+
"model.layers.1.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
31 |
+
"model.layers.10.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
32 |
+
"model.layers.10.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
33 |
+
"model.layers.10.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
34 |
+
"model.layers.10.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
35 |
+
"model.layers.10.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
36 |
+
"model.layers.10.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
37 |
+
"model.layers.10.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
38 |
+
"model.layers.10.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
39 |
+
"model.layers.10.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
40 |
+
"model.layers.10.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
41 |
+
"model.layers.10.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
42 |
+
"model.layers.10.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
43 |
+
"model.layers.11.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
44 |
+
"model.layers.11.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
45 |
+
"model.layers.11.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
46 |
+
"model.layers.11.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
47 |
+
"model.layers.11.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
48 |
+
"model.layers.11.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
49 |
+
"model.layers.11.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
50 |
+
"model.layers.11.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
51 |
+
"model.layers.11.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
52 |
+
"model.layers.11.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
53 |
+
"model.layers.11.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
54 |
+
"model.layers.11.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
55 |
+
"model.layers.12.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
56 |
+
"model.layers.12.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
57 |
+
"model.layers.12.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
58 |
+
"model.layers.12.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
59 |
+
"model.layers.12.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
60 |
+
"model.layers.12.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
61 |
+
"model.layers.12.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
62 |
+
"model.layers.12.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
63 |
+
"model.layers.12.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
64 |
+
"model.layers.12.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
65 |
+
"model.layers.12.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
66 |
+
"model.layers.12.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
67 |
+
"model.layers.13.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
68 |
+
"model.layers.13.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
69 |
+
"model.layers.13.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
70 |
+
"model.layers.13.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
71 |
+
"model.layers.13.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
72 |
+
"model.layers.13.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
73 |
+
"model.layers.13.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
74 |
+
"model.layers.13.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
75 |
+
"model.layers.13.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
76 |
+
"model.layers.13.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
77 |
+
"model.layers.13.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
78 |
+
"model.layers.13.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
79 |
+
"model.layers.14.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
80 |
+
"model.layers.14.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
81 |
+
"model.layers.14.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
82 |
+
"model.layers.14.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
83 |
+
"model.layers.14.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
84 |
+
"model.layers.14.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
85 |
+
"model.layers.14.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
86 |
+
"model.layers.14.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
87 |
+
"model.layers.14.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
88 |
+
"model.layers.14.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
89 |
+
"model.layers.14.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
90 |
+
"model.layers.14.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
91 |
+
"model.layers.15.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
92 |
+
"model.layers.15.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
93 |
+
"model.layers.15.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
94 |
+
"model.layers.15.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
95 |
+
"model.layers.15.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
96 |
+
"model.layers.15.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
97 |
+
"model.layers.15.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
98 |
+
"model.layers.15.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
99 |
+
"model.layers.15.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
100 |
+
"model.layers.15.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
101 |
+
"model.layers.15.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
102 |
+
"model.layers.15.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
103 |
+
"model.layers.16.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
104 |
+
"model.layers.16.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
105 |
+
"model.layers.16.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
106 |
+
"model.layers.16.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
107 |
+
"model.layers.16.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
108 |
+
"model.layers.16.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
109 |
+
"model.layers.16.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
110 |
+
"model.layers.16.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
111 |
+
"model.layers.16.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
112 |
+
"model.layers.16.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
113 |
+
"model.layers.16.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
114 |
+
"model.layers.16.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
115 |
+
"model.layers.17.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
116 |
+
"model.layers.17.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
117 |
+
"model.layers.17.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
118 |
+
"model.layers.17.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
119 |
+
"model.layers.17.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
120 |
+
"model.layers.17.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
121 |
+
"model.layers.17.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
122 |
+
"model.layers.17.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
123 |
+
"model.layers.17.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
124 |
+
"model.layers.17.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
125 |
+
"model.layers.17.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
126 |
+
"model.layers.17.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
127 |
+
"model.layers.18.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
128 |
+
"model.layers.18.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
129 |
+
"model.layers.18.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
130 |
+
"model.layers.18.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
131 |
+
"model.layers.18.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
132 |
+
"model.layers.18.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
133 |
+
"model.layers.18.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
134 |
+
"model.layers.18.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
135 |
+
"model.layers.18.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
136 |
+
"model.layers.18.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
137 |
+
"model.layers.18.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
138 |
+
"model.layers.18.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
139 |
+
"model.layers.19.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
140 |
+
"model.layers.19.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
141 |
+
"model.layers.19.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
142 |
+
"model.layers.19.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
143 |
+
"model.layers.19.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
144 |
+
"model.layers.19.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
145 |
+
"model.layers.19.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
146 |
+
"model.layers.19.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
147 |
+
"model.layers.19.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
148 |
+
"model.layers.19.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
149 |
+
"model.layers.19.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
150 |
+
"model.layers.19.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
151 |
+
"model.layers.2.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
152 |
+
"model.layers.2.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
153 |
+
"model.layers.2.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
154 |
+
"model.layers.2.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
155 |
+
"model.layers.2.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
156 |
+
"model.layers.2.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
157 |
+
"model.layers.2.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
158 |
+
"model.layers.2.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
159 |
+
"model.layers.2.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
160 |
+
"model.layers.2.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
161 |
+
"model.layers.2.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
162 |
+
"model.layers.2.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
163 |
+
"model.layers.20.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
164 |
+
"model.layers.20.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
165 |
+
"model.layers.20.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
166 |
+
"model.layers.20.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
167 |
+
"model.layers.20.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
168 |
+
"model.layers.20.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
169 |
+
"model.layers.20.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
170 |
+
"model.layers.20.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
171 |
+
"model.layers.20.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
172 |
+
"model.layers.20.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
173 |
+
"model.layers.20.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
174 |
+
"model.layers.20.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
175 |
+
"model.layers.21.input_layernorm.weight": "pytorch_model-00002-of-00002.bin",
|
176 |
+
"model.layers.21.mlp.down_proj.weight": "pytorch_model-00002-of-00002.bin",
|
177 |
+
"model.layers.21.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
178 |
+
"model.layers.21.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
179 |
+
"model.layers.21.post_attention_layernorm.weight": "pytorch_model-00002-of-00002.bin",
|
180 |
+
"model.layers.21.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
181 |
+
"model.layers.21.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
182 |
+
"model.layers.21.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
183 |
+
"model.layers.21.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
184 |
+
"model.layers.21.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
185 |
+
"model.layers.21.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
186 |
+
"model.layers.21.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
187 |
+
"model.layers.22.input_layernorm.weight": "pytorch_model-00002-of-00002.bin",
|
188 |
+
"model.layers.22.mlp.down_proj.weight": "pytorch_model-00002-of-00002.bin",
|
189 |
+
"model.layers.22.mlp.gate_proj.weight": "pytorch_model-00002-of-00002.bin",
|
190 |
+
"model.layers.22.mlp.up_proj.weight": "pytorch_model-00002-of-00002.bin",
|
191 |
+
"model.layers.22.post_attention_layernorm.weight": "pytorch_model-00002-of-00002.bin",
|
192 |
+
"model.layers.22.self_attn.k_proj.bias": "pytorch_model-00002-of-00002.bin",
|
193 |
+
"model.layers.22.self_attn.k_proj.weight": "pytorch_model-00002-of-00002.bin",
|
194 |
+
"model.layers.22.self_attn.o_proj.weight": "pytorch_model-00002-of-00002.bin",
|
195 |
+
"model.layers.22.self_attn.q_proj.bias": "pytorch_model-00002-of-00002.bin",
|
196 |
+
"model.layers.22.self_attn.q_proj.weight": "pytorch_model-00002-of-00002.bin",
|
197 |
+
"model.layers.22.self_attn.v_proj.bias": "pytorch_model-00002-of-00002.bin",
|
198 |
+
"model.layers.22.self_attn.v_proj.weight": "pytorch_model-00002-of-00002.bin",
|
199 |
+
"model.layers.23.input_layernorm.weight": "pytorch_model-00002-of-00002.bin",
|
200 |
+
"model.layers.23.mlp.down_proj.weight": "pytorch_model-00002-of-00002.bin",
|
201 |
+
"model.layers.23.mlp.gate_proj.weight": "pytorch_model-00002-of-00002.bin",
|
202 |
+
"model.layers.23.mlp.up_proj.weight": "pytorch_model-00002-of-00002.bin",
|
203 |
+
"model.layers.23.post_attention_layernorm.weight": "pytorch_model-00002-of-00002.bin",
|
204 |
+
"model.layers.23.self_attn.k_proj.bias": "pytorch_model-00002-of-00002.bin",
|
205 |
+
"model.layers.23.self_attn.k_proj.weight": "pytorch_model-00002-of-00002.bin",
|
206 |
+
"model.layers.23.self_attn.o_proj.weight": "pytorch_model-00002-of-00002.bin",
|
207 |
+
"model.layers.23.self_attn.q_proj.bias": "pytorch_model-00002-of-00002.bin",
|
208 |
+
"model.layers.23.self_attn.q_proj.weight": "pytorch_model-00002-of-00002.bin",
|
209 |
+
"model.layers.23.self_attn.v_proj.bias": "pytorch_model-00002-of-00002.bin",
|
210 |
+
"model.layers.23.self_attn.v_proj.weight": "pytorch_model-00002-of-00002.bin",
|
211 |
+
"model.layers.24.input_layernorm.weight": "pytorch_model-00002-of-00002.bin",
|
212 |
+
"model.layers.24.mlp.down_proj.weight": "pytorch_model-00002-of-00002.bin",
|
213 |
+
"model.layers.24.mlp.gate_proj.weight": "pytorch_model-00002-of-00002.bin",
|
214 |
+
"model.layers.24.mlp.up_proj.weight": "pytorch_model-00002-of-00002.bin",
|
215 |
+
"model.layers.24.post_attention_layernorm.weight": "pytorch_model-00002-of-00002.bin",
|
216 |
+
"model.layers.24.self_attn.k_proj.bias": "pytorch_model-00002-of-00002.bin",
|
217 |
+
"model.layers.24.self_attn.k_proj.weight": "pytorch_model-00002-of-00002.bin",
|
218 |
+
"model.layers.24.self_attn.o_proj.weight": "pytorch_model-00002-of-00002.bin",
|
219 |
+
"model.layers.24.self_attn.q_proj.bias": "pytorch_model-00002-of-00002.bin",
|
220 |
+
"model.layers.24.self_attn.q_proj.weight": "pytorch_model-00002-of-00002.bin",
|
221 |
+
"model.layers.24.self_attn.v_proj.bias": "pytorch_model-00002-of-00002.bin",
|
222 |
+
"model.layers.24.self_attn.v_proj.weight": "pytorch_model-00002-of-00002.bin",
|
223 |
+
"model.layers.25.input_layernorm.weight": "pytorch_model-00002-of-00002.bin",
|
224 |
+
"model.layers.25.mlp.down_proj.weight": "pytorch_model-00002-of-00002.bin",
|
225 |
+
"model.layers.25.mlp.gate_proj.weight": "pytorch_model-00002-of-00002.bin",
|
226 |
+
"model.layers.25.mlp.up_proj.weight": "pytorch_model-00002-of-00002.bin",
|
227 |
+
"model.layers.25.post_attention_layernorm.weight": "pytorch_model-00002-of-00002.bin",
|
228 |
+
"model.layers.25.self_attn.k_proj.bias": "pytorch_model-00002-of-00002.bin",
|
229 |
+
"model.layers.25.self_attn.k_proj.weight": "pytorch_model-00002-of-00002.bin",
|
230 |
+
"model.layers.25.self_attn.o_proj.weight": "pytorch_model-00002-of-00002.bin",
|
231 |
+
"model.layers.25.self_attn.q_proj.bias": "pytorch_model-00002-of-00002.bin",
|
232 |
+
"model.layers.25.self_attn.q_proj.weight": "pytorch_model-00002-of-00002.bin",
|
233 |
+
"model.layers.25.self_attn.v_proj.bias": "pytorch_model-00002-of-00002.bin",
|
234 |
+
"model.layers.25.self_attn.v_proj.weight": "pytorch_model-00002-of-00002.bin",
|
235 |
+
"model.layers.26.input_layernorm.weight": "pytorch_model-00002-of-00002.bin",
|
236 |
+
"model.layers.26.mlp.down_proj.weight": "pytorch_model-00002-of-00002.bin",
|
237 |
+
"model.layers.26.mlp.gate_proj.weight": "pytorch_model-00002-of-00002.bin",
|
238 |
+
"model.layers.26.mlp.up_proj.weight": "pytorch_model-00002-of-00002.bin",
|
239 |
+
"model.layers.26.post_attention_layernorm.weight": "pytorch_model-00002-of-00002.bin",
|
240 |
+
"model.layers.26.self_attn.k_proj.bias": "pytorch_model-00002-of-00002.bin",
|
241 |
+
"model.layers.26.self_attn.k_proj.weight": "pytorch_model-00002-of-00002.bin",
|
242 |
+
"model.layers.26.self_attn.o_proj.weight": "pytorch_model-00002-of-00002.bin",
|
243 |
+
"model.layers.26.self_attn.q_proj.bias": "pytorch_model-00002-of-00002.bin",
|
244 |
+
"model.layers.26.self_attn.q_proj.weight": "pytorch_model-00002-of-00002.bin",
|
245 |
+
"model.layers.26.self_attn.v_proj.bias": "pytorch_model-00002-of-00002.bin",
|
246 |
+
"model.layers.26.self_attn.v_proj.weight": "pytorch_model-00002-of-00002.bin",
|
247 |
+
"model.layers.27.input_layernorm.weight": "pytorch_model-00002-of-00002.bin",
|
248 |
+
"model.layers.27.mlp.down_proj.weight": "pytorch_model-00002-of-00002.bin",
|
249 |
+
"model.layers.27.mlp.gate_proj.weight": "pytorch_model-00002-of-00002.bin",
|
250 |
+
"model.layers.27.mlp.up_proj.weight": "pytorch_model-00002-of-00002.bin",
|
251 |
+
"model.layers.27.post_attention_layernorm.weight": "pytorch_model-00002-of-00002.bin",
|
252 |
+
"model.layers.27.self_attn.k_proj.bias": "pytorch_model-00002-of-00002.bin",
|
253 |
+
"model.layers.27.self_attn.k_proj.weight": "pytorch_model-00002-of-00002.bin",
|
254 |
+
"model.layers.27.self_attn.o_proj.weight": "pytorch_model-00002-of-00002.bin",
|
255 |
+
"model.layers.27.self_attn.q_proj.bias": "pytorch_model-00002-of-00002.bin",
|
256 |
+
"model.layers.27.self_attn.q_proj.weight": "pytorch_model-00002-of-00002.bin",
|
257 |
+
"model.layers.27.self_attn.v_proj.bias": "pytorch_model-00002-of-00002.bin",
|
258 |
+
"model.layers.27.self_attn.v_proj.weight": "pytorch_model-00002-of-00002.bin",
|
259 |
+
"model.layers.3.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
260 |
+
"model.layers.3.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
261 |
+
"model.layers.3.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
262 |
+
"model.layers.3.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
263 |
+
"model.layers.3.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
264 |
+
"model.layers.3.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
265 |
+
"model.layers.3.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
266 |
+
"model.layers.3.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
267 |
+
"model.layers.3.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
268 |
+
"model.layers.3.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
269 |
+
"model.layers.3.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
270 |
+
"model.layers.3.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
271 |
+
"model.layers.4.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
272 |
+
"model.layers.4.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
273 |
+
"model.layers.4.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
274 |
+
"model.layers.4.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
275 |
+
"model.layers.4.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
276 |
+
"model.layers.4.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
277 |
+
"model.layers.4.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
278 |
+
"model.layers.4.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
279 |
+
"model.layers.4.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
280 |
+
"model.layers.4.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
281 |
+
"model.layers.4.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
282 |
+
"model.layers.4.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
283 |
+
"model.layers.5.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
284 |
+
"model.layers.5.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
285 |
+
"model.layers.5.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
286 |
+
"model.layers.5.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
287 |
+
"model.layers.5.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
288 |
+
"model.layers.5.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
289 |
+
"model.layers.5.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
290 |
+
"model.layers.5.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
291 |
+
"model.layers.5.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
292 |
+
"model.layers.5.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
293 |
+
"model.layers.5.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
294 |
+
"model.layers.5.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
295 |
+
"model.layers.6.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
296 |
+
"model.layers.6.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
297 |
+
"model.layers.6.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
298 |
+
"model.layers.6.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
299 |
+
"model.layers.6.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
300 |
+
"model.layers.6.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
301 |
+
"model.layers.6.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
302 |
+
"model.layers.6.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
303 |
+
"model.layers.6.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
304 |
+
"model.layers.6.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
305 |
+
"model.layers.6.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
306 |
+
"model.layers.6.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
307 |
+
"model.layers.7.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
308 |
+
"model.layers.7.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
309 |
+
"model.layers.7.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
310 |
+
"model.layers.7.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
311 |
+
"model.layers.7.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
312 |
+
"model.layers.7.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
313 |
+
"model.layers.7.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
314 |
+
"model.layers.7.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
315 |
+
"model.layers.7.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
316 |
+
"model.layers.7.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
317 |
+
"model.layers.7.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
318 |
+
"model.layers.7.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
319 |
+
"model.layers.8.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
320 |
+
"model.layers.8.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
321 |
+
"model.layers.8.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
322 |
+
"model.layers.8.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
323 |
+
"model.layers.8.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
324 |
+
"model.layers.8.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
325 |
+
"model.layers.8.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
326 |
+
"model.layers.8.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
327 |
+
"model.layers.8.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
328 |
+
"model.layers.8.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
329 |
+
"model.layers.8.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
330 |
+
"model.layers.8.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
331 |
+
"model.layers.9.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
332 |
+
"model.layers.9.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
333 |
+
"model.layers.9.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
334 |
+
"model.layers.9.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
335 |
+
"model.layers.9.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
336 |
+
"model.layers.9.self_attn.k_proj.bias": "pytorch_model-00001-of-00002.bin",
|
337 |
+
"model.layers.9.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
338 |
+
"model.layers.9.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
339 |
+
"model.layers.9.self_attn.q_proj.bias": "pytorch_model-00001-of-00002.bin",
|
340 |
+
"model.layers.9.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
341 |
+
"model.layers.9.self_attn.v_proj.bias": "pytorch_model-00001-of-00002.bin",
|
342 |
+
"model.layers.9.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
343 |
+
"model.norm.weight": "pytorch_model-00002-of-00002.bin",
|
344 |
+
"score.bias": "pytorch_model-00002-of-00002.bin",
|
345 |
+
"score.weight": "pytorch_model-00002-of-00002.bin"
|
346 |
+
}
|
347 |
+
}
|
special_tokens_map.json
ADDED
@@ -0,0 +1,42 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"additional_special_tokens": [
|
3 |
+
"<|im_start|>",
|
4 |
+
"<|im_end|>"
|
5 |
+
],
|
6 |
+
"cls_token": {
|
7 |
+
"content": "<|im_start|>",
|
8 |
+
"lstrip": false,
|
9 |
+
"normalized": false,
|
10 |
+
"rstrip": false,
|
11 |
+
"single_word": false
|
12 |
+
},
|
13 |
+
"eos_token": {
|
14 |
+
"content": "<|endoftext|>",
|
15 |
+
"lstrip": false,
|
16 |
+
"normalized": false,
|
17 |
+
"rstrip": false,
|
18 |
+
"single_word": false
|
19 |
+
},
|
20 |
+
"mask_token": "<unk>",
|
21 |
+
"pad_token": {
|
22 |
+
"content": "<|endoftext|>",
|
23 |
+
"lstrip": false,
|
24 |
+
"normalized": false,
|
25 |
+
"rstrip": false,
|
26 |
+
"single_word": false
|
27 |
+
},
|
28 |
+
"sep_token": {
|
29 |
+
"content": "<|im_end|>",
|
30 |
+
"lstrip": false,
|
31 |
+
"normalized": false,
|
32 |
+
"rstrip": false,
|
33 |
+
"single_word": false
|
34 |
+
},
|
35 |
+
"unk_token": {
|
36 |
+
"content": "<unk>",
|
37 |
+
"lstrip": false,
|
38 |
+
"normalized": false,
|
39 |
+
"rstrip": false,
|
40 |
+
"single_word": false
|
41 |
+
}
|
42 |
+
}
|
tokenizer_config.json
ADDED
@@ -0,0 +1,54 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"add_prefix_space": false,
|
3 |
+
"added_tokens_decoder": {
|
4 |
+
"128244": {
|
5 |
+
"content": "<unk>",
|
6 |
+
"lstrip": false,
|
7 |
+
"normalized": false,
|
8 |
+
"rstrip": false,
|
9 |
+
"single_word": false,
|
10 |
+
"special": true
|
11 |
+
},
|
12 |
+
"151643": {
|
13 |
+
"content": "<|endoftext|>",
|
14 |
+
"lstrip": false,
|
15 |
+
"normalized": false,
|
16 |
+
"rstrip": false,
|
17 |
+
"single_word": false,
|
18 |
+
"special": true
|
19 |
+
},
|
20 |
+
"151644": {
|
21 |
+
"content": "<|im_start|>",
|
22 |
+
"lstrip": false,
|
23 |
+
"normalized": false,
|
24 |
+
"rstrip": false,
|
25 |
+
"single_word": false,
|
26 |
+
"special": true
|
27 |
+
},
|
28 |
+
"151645": {
|
29 |
+
"content": "<|im_end|>",
|
30 |
+
"lstrip": false,
|
31 |
+
"normalized": false,
|
32 |
+
"rstrip": false,
|
33 |
+
"single_word": false,
|
34 |
+
"special": true
|
35 |
+
}
|
36 |
+
},
|
37 |
+
"additional_special_tokens": [
|
38 |
+
"<|im_start|>",
|
39 |
+
"<|im_end|>"
|
40 |
+
],
|
41 |
+
"bos_token": null,
|
42 |
+
"clean_up_tokenization_spaces": false,
|
43 |
+
"cls_token": "<|im_start|>",
|
44 |
+
"eos_token": "<|endoftext|>",
|
45 |
+
"errors": "replace",
|
46 |
+
"mask_token": "<unk>",
|
47 |
+
"model_max_length": 32768,
|
48 |
+
"pad_token": "<|endoftext|>",
|
49 |
+
"padding_side": "right",
|
50 |
+
"sep_token": "<|im_end|>",
|
51 |
+
"split_special_tokens": false,
|
52 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
53 |
+
"unk_token": "<unk>"
|
54 |
+
}
|
ud.py
ADDED
@@ -0,0 +1,121 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import numpy
|
2 |
+
from transformers import TokenClassificationPipeline
|
3 |
+
|
4 |
+
class BellmanFordTokenClassificationPipeline(TokenClassificationPipeline):
|
5 |
+
def __init__(self,**kwargs):
|
6 |
+
super().__init__(**kwargs)
|
7 |
+
x=self.model.config.label2id
|
8 |
+
y=[k for k in x if k.startswith("B-") or not (k.startswith("I-") or k.endswith("|root") or k.find("|l-")>0 or k.find("|r-")>0)]
|
9 |
+
self.transition=numpy.full((len(x),len(x)),numpy.nan)
|
10 |
+
for k,v in x.items():
|
11 |
+
for j in ["I-"+k[2:]] if k.startswith("B-") else [k]+y if k.startswith("I-") else y:
|
12 |
+
self.transition[v,x[j]]=0
|
13 |
+
def check_model_type(self,supported_models):
|
14 |
+
pass
|
15 |
+
def postprocess(self,model_outputs,**kwargs):
|
16 |
+
if "logits" not in model_outputs:
|
17 |
+
return self.postprocess(model_outputs[0],**kwargs)
|
18 |
+
m=model_outputs["logits"][0].numpy()
|
19 |
+
e=numpy.exp(m-numpy.max(m,axis=-1,keepdims=True))
|
20 |
+
z=e/e.sum(axis=-1,keepdims=True)
|
21 |
+
for i in range(m.shape[0]-1,0,-1):
|
22 |
+
m[i-1]+=numpy.nanmax(m[i]+self.transition,axis=1)
|
23 |
+
k=[numpy.nanargmax(m[0]+self.transition[0])]
|
24 |
+
for i in range(1,m.shape[0]):
|
25 |
+
k.append(numpy.nanargmax(m[i]+self.transition[k[-1]]))
|
26 |
+
w=[{"entity":self.model.config.id2label[j],"start":s,"end":e,"score":z[i,j]} for i,((s,e),j) in enumerate(zip(model_outputs["offset_mapping"][0].tolist(),k)) if s<e]
|
27 |
+
if "aggregation_strategy" in kwargs and kwargs["aggregation_strategy"]!="none":
|
28 |
+
for i,t in reversed(list(enumerate(w))):
|
29 |
+
p=t.pop("entity")
|
30 |
+
if p.startswith("I-"):
|
31 |
+
w[i-1]["score"]=min(w[i-1]["score"],t["score"])
|
32 |
+
w[i-1]["end"]=w.pop(i)["end"]
|
33 |
+
elif p.startswith("B-"):
|
34 |
+
t["entity_group"]=p[2:]
|
35 |
+
else:
|
36 |
+
t["entity_group"]=p
|
37 |
+
for t in w:
|
38 |
+
t["text"]=model_outputs["sentence"][t["start"]:t["end"]]
|
39 |
+
return w
|
40 |
+
|
41 |
+
class UniversalDependenciesCausalPipeline(BellmanFordTokenClassificationPipeline):
|
42 |
+
def __init__(self,**kwargs):
|
43 |
+
kwargs["aggregation_strategy"]="simple"
|
44 |
+
super().__init__(**kwargs)
|
45 |
+
x=self.model.config.label2id
|
46 |
+
self.root=numpy.full((len(x)),numpy.nan)
|
47 |
+
self.left_arc=numpy.full((len(x)),numpy.nan)
|
48 |
+
self.right_arc=numpy.full((len(x)),numpy.nan)
|
49 |
+
for k,v in x.items():
|
50 |
+
if k.endswith("|root"):
|
51 |
+
self.root[v]=0
|
52 |
+
elif k.find("|l-")>0:
|
53 |
+
self.left_arc[v]=0
|
54 |
+
elif k.find("|r-")>0:
|
55 |
+
self.right_arc[v]=0
|
56 |
+
def postprocess(self,model_outputs,**kwargs):
|
57 |
+
import torch
|
58 |
+
if "logits" not in model_outputs:
|
59 |
+
return self.postprocess(model_outputs[0],**kwargs)
|
60 |
+
m=model_outputs["logits"][0].numpy()
|
61 |
+
for i in range(m.shape[0]-1,0,-1):
|
62 |
+
m[i-1]+=numpy.nanmax(m[i]+self.transition,axis=1)
|
63 |
+
k=[numpy.nanargmax(m[0]+self.transition[0])]
|
64 |
+
for i in range(1,m.shape[0]):
|
65 |
+
k.append(numpy.nanargmax(m[i]+self.transition[k[-1]]))
|
66 |
+
w=[{"entity":self.model.config.id2label[j],"start":s,"end":e} for i,((s,e),j) in enumerate(zip(model_outputs["offset_mapping"][0].tolist(),k)) if s<e]
|
67 |
+
for i,t in reversed(list(enumerate(w))):
|
68 |
+
p=t.pop("entity")
|
69 |
+
if p.startswith("I-"):
|
70 |
+
w[i-1]["end"]=w.pop(i)["end"]
|
71 |
+
elif p.startswith("B-"):
|
72 |
+
t["entity_group"]=p[2:]
|
73 |
+
else:
|
74 |
+
t["entity_group"]=p
|
75 |
+
d=[model_outputs["sentence"][t["start"]:t["end"]] for t in w]
|
76 |
+
v=self.tokenizer(d,add_special_tokens=False)
|
77 |
+
e=self.model.get_input_embeddings().weight
|
78 |
+
m=[]
|
79 |
+
for x in v["input_ids"]:
|
80 |
+
if x==[]:
|
81 |
+
x=[self.tokenizer.unk_token_id]
|
82 |
+
m.append(e[x,:].sum(axis=0))
|
83 |
+
m.append(e[self.tokenizer.sep_token_id,:])
|
84 |
+
m.append(e[self.tokenizer.pad_token_id,:])
|
85 |
+
m=torch.stack(m)
|
86 |
+
k=list(range(len(d)+1))
|
87 |
+
with torch.no_grad():
|
88 |
+
e=self.model(inputs_embeds=torch.stack([m[k+list(range(i,len(d)))+[-1]*i,:] for i in range(len(d))])).logits[:,-len(d):,:].numpy()
|
89 |
+
for i in range(len(d)):
|
90 |
+
for j in range(i):
|
91 |
+
e[-j-1,-i-1],e[-i-1,-j-1]=e[-i-1,i-j]+self.left_arc,e[-i-1,i-j]+self.right_arc
|
92 |
+
e[-i-1,-i-1]=e[-i-1,0]+self.root
|
93 |
+
m,p=numpy.nanmax(e,axis=2),numpy.nanargmax(e,axis=2)
|
94 |
+
h=self.chu_liu_edmonds(m)
|
95 |
+
z=[i for i,j in enumerate(h) if i==j]
|
96 |
+
if len(z)>1:
|
97 |
+
k,h=z[numpy.nanargmax(m[z,z])],numpy.nanmin(m)-numpy.nanmax(m)
|
98 |
+
m[:,z]+=[[0 if j in z and (i!=j or i==k) else h for i in z] for j in range(m.shape[0])]
|
99 |
+
h=self.chu_liu_edmonds(m)
|
100 |
+
q=[self.model.config.id2label[p[j,i]].split("|") for i,j in enumerate(h)]
|
101 |
+
t=model_outputs["sentence"].replace("\n"," ")
|
102 |
+
u="# text = "+t+"\n"
|
103 |
+
for i,j in enumerate(d):
|
104 |
+
u+="\t".join([str(i+1),j,"_",q[i][0],"_","_" if len(q[i])<3 else "|".join(q[i][1:-1]),str(0 if h[i]==i else h[i]+1),"root" if q[i][-1]=="root" else q[i][-1][2:],"_","_" if i+1<len(d) and w[i]["end"]<w[i+1]["start"] else "SpaceAfter=No"])+"\n"
|
105 |
+
return u+"\n"
|
106 |
+
def chu_liu_edmonds(self,matrix):
|
107 |
+
h=numpy.nanargmax(matrix,axis=0)
|
108 |
+
x=[-1 if i==j else j for i,j in enumerate(h)]
|
109 |
+
for b in [lambda x,i,j:-1 if i not in x else x[i],lambda x,i,j:-1 if j<0 else x[j]]:
|
110 |
+
y=[]
|
111 |
+
while x!=y:
|
112 |
+
y=list(x)
|
113 |
+
for i,j in enumerate(x):
|
114 |
+
x[i]=b(x,i,j)
|
115 |
+
if max(x)<0:
|
116 |
+
return h
|
117 |
+
y,x=[i for i,j in enumerate(x) if j==max(x)],[i for i,j in enumerate(x) if j<max(x)]
|
118 |
+
z=matrix-numpy.nanmax(matrix,axis=0)
|
119 |
+
m=numpy.block([[z[x,:][:,x],numpy.nanmax(z[x,:][:,y],axis=1).reshape(len(x),1)],[numpy.nanmax(z[y,:][:,x],axis=0),numpy.nanmax(z[y,y])]])
|
120 |
+
k=[j if i==len(x) else x[j] if j<len(x) else y[numpy.nanargmax(z[y,x[i]])] for i,j in enumerate(self.chu_liu_edmonds(m))]
|
121 |
+
|
vocab.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|