πΆ Beagle
Collection
Merges done using mergekit and LazyMergekit: https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb#scrollTo=d5mYzDo1q96y
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8 items
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Updated
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6
Daredevil-7B is a merge of the following models using LazyMergekit:
TBD.
Model | AGIEval | GPT4All | TruthfulQA | Bigbench | Average |
---|---|---|---|---|---|
Daredevil-7B | 44.85 | 76.07 | 64.89 | 47.07 | 58.22 |
OpenHermes-2.5-Mistral-7B | 42.75 | 72.99 | 52.99 | 40.94 | 52.42 |
NeuralHermes-2.5-Mistral-7B | 43.67 | 73.24 | 55.37 | 41.76 | 53.51 |
Nous-Hermes-2-SOLAR-10.7B | 47.79 | 74.69 | 55.92 | 44.84 | 55.81 |
Marcoro14-7B-slerp | 44.66 | 76.24 | 64.15 | 45.64 | 57.67 |
CatMarcoro14-7B-slerp | 45.21 | 75.91 | 63.81 | 47.31 | 58.06 |
See the complete evaluation here.
models:
- model: mistralai/Mistral-7B-v0.1
# No parameters necessary for base model
- model: samir-fama/SamirGPT-v1
parameters:
density: 0.53
weight: 0.4
- model: abacusai/Slerp-CM-mist-dpo
parameters:
density: 0.53
weight: 0.3
- model: EmbeddedLLM/Mistral-7B-Merge-14-v0.2
parameters:
density: 0.53
weight: 0.3
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
int8_mask: true
dtype: bfloat16
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "shadowml/Daredevil-7B"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 73.36 |
AI2 Reasoning Challenge (25-Shot) | 69.37 |
HellaSwag (10-Shot) | 87.17 |
MMLU (5-Shot) | 65.30 |
TruthfulQA (0-shot) | 64.09 |
Winogrande (5-shot) | 81.29 |
GSM8k (5-shot) | 72.93 |