🤝Mistral 7B-v1 Merges
Collection
Trying and comparing all merge methods on 3 Mistral-7B models
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4 items
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Updated
TriMistral-7B-DARETIES is a merge of the following models using LazyMergekit:
models:
- model: HuggingFaceH4/zephyr-7b-beta
# No parameters necessary for base model
- model: NousResearch/Hermes-2-Pro-Mistral-7B
parameters:
density: 0.53
weight: 0.4
- model: instructlab/merlinite-7b-lab
parameters:
density: 0.53
weight: 0.3
merge_method: dare_ties
base_model: HuggingFaceH4/zephyr-7b-beta
parameters:
int8_mask: true
dtype: bfloat16
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Muhammad2003/TriMistral-7B-DARETIES"
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. | 68.41 |
AI2 Reasoning Challenge (25-Shot) | 65.19 |
HellaSwag (10-Shot) | 85.40 |
MMLU (5-Shot) | 64.35 |
TruthfulQA (0-shot) | 56.64 |
Winogrande (5-shot) | 78.30 |
GSM8k (5-shot) | 60.58 |