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---
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|
|