models:
  - model: HuggingFaceH4/zephyr-7b-beta
  - model: NousResearch/Hermes-2-Pro-Mistral-7B
  - model: instructlab/merlinite-7b-lab
merge_method: model_stock
base_model: HuggingFaceH4/zephyr-7b-beta
dtype: float16

💻 Usage

python

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Muhammad2003/TriMistral-7B-MODELSTOCK"
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"])

🏆 Evaluation

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	67.15
AI2 Reasoning Challenge (25-Shot)	64.68
HellaSwag (10-Shot)	85.64
MMLU (5-Shot)	64.21
TruthfulQA (0-shot)	57.24
Winogrande (5-shot)	78.69
GSM8k (5-shot)	52.46