---
license: apache-2.0
tags:
- merge
---

# mistral-7b-merged-dare

mistral-7b-merged-dare is a merge of the following models:


## 🧩 Configuration

```yaml
models:
  - model: mistralai/Mistral-7B-v0.1
  - 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

```

## 💻 Usage
```python
!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "mayacinka/West-Ramen-7Bx4"

tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
)

messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_mychen76__mistral-7b-merged-dare)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |73.46|
|AI2 Reasoning Challenge (25-Shot)|69.71|
|HellaSwag (10-Shot)              |87.05|
|MMLU (5-Shot)                    |65.07|
|TruthfulQA (0-shot)              |63.24|
|Winogrande (5-shot)              |81.61|
|GSM8k (5-shot)                   |73.01|