BAAI
/

File size: 1,671 Bytes
3713fdc
 
 
 
 
 
 
 
 
 
7649611
 
3713fdc
 
 
1df336d
3713fdc
1df336d
3713fdc
1df336d
3713fdc
9ea5277
3713fdc
9ea5277
 
 
 
3713fdc
 
 
 
 
1df336d
3713fdc
 
 
 
 
091bd28
3713fdc
 
 
 
 
 
 
 
 
9ea5277
3713fdc
1c0b24c
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
---
license: other
---


![Aquila_logo](./log.jpeg)


<h4 align="center">
    <p>
        <a href="https://huggingface.co/BAAI/AquilaChat2-7B/blob/main/README.md">English</a> 
        <b>简体中文</b> |
    </p>
</h4>

# 悟道·天鹰(Aquila2)

我们开源了我们的 **Aquila2** 系列,现在包括基础语言模型 **Aquila2-7B****Aquila2-34B** ,对话模型 **AquilaChat2-7B****AquilaChat2-34B**,长文本对话模型**AquilaChat2-7B-16k****AquilaChat2-34B-16k**

悟道 · 天鹰 Aquila 模型的更多细节将在官方技术报告中呈现。请关注官方渠道更新。

## 快速开始使用 AquilaChat2-7B


## 使用方式/How to use

### 1. 推理/Inference

```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
device = torch.device("cuda")
model_info = "BAAI/AquilaChat2-7B"
tokenizer = AutoTokenizer.from_pretrained(model_info, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_info, trust_remote_code=True)
model.eval()
model.to(device)
text = "请给出10个要到北京旅游的理由。"
tokens = tokenizer.encode_plus(text)['input_ids']
tokens = torch.tensor(tokens)[None,].to(device)
stop_tokens = ["###", "[UNK]", "</s>"]
with torch.no_grad():
    out = model.generate(tokens, do_sample=True, max_length=512, eos_token_id=100007, bad_words_ids=[[tokenizer.encode(token)[0] for token in stop_tokens]])[0]
    out = tokenizer.decode(out.cpu().numpy().tolist())
    print(out)
```


## 证书/License

Aquila2系列开源模型使用 [智源Aquila系列模型许可协议](https://huggingface.co/BAAI/Aquila2-70B/blob/main/BAAI-Aquila-Model-License-Agreement.pdf)