SnorkelWestBeagle-DARETIES-7B
SnorkelWestBeagle-DARETIES-7B is a merge of the following models using LazyMergekit:
🧩 Configuration
models:
- model: mistralai/Mistral-7B-v0.1
# no parameters necessary for base model
- model: snorkelai/Snorkel-Mistral-PairRM-DPO
parameters:
density: 0.55
weight: 0.3
- model: senseable/WestLake-7B-v2
parameters:
density: 0.65
weight: 0.4
- model: mlabonne/NeuralBeagle14-7B
parameters:
density: 0.45
weight: 0.3
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
int8_mask: true
dtype: float16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "jsfs11/SnorkelWestBeagle-DARETIES-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"])
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 73.03 |
AI2 Reasoning Challenge (25-Shot) | 71.16 |
HellaSwag (10-Shot) | 87.35 |
MMLU (5-Shot) | 64.35 |
TruthfulQA (0-shot) | 70.05 |
Winogrande (5-shot) | 83.19 |
GSM8k (5-shot) | 62.09 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard71.160
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard87.350
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.350
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard70.050
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard83.190
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard62.090