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

# openmixtral-6x7b-v2

Quantized openmixtral-6x7b-merged_v2 is a merge of the following 6x7B models:

## 🧩 Configuration

```yaml
base_model: mlabonne/Marcoro14-7B-slerp
experts:
  - source_model: openchat/openchat-3.5-1210
    positive_prompts:
    - "chat"
    - "assistant"
    - "tell me"
    - "explain"
  - source_model: Weyaxi/Einstein-v4-7B
    positive_prompts:
    - "physics"
    - "biology"
    - "chemistry"
    - "science"    
  - source_model: BioMistral/BioMistral-7B
    positive_prompts:
    - "medical"
    - "pubmed"
    - "healthcare"
    - "health"        
  - source_model: beowolx/CodeNinja-1.0-OpenChat-7B
    positive_prompts:
    - "code"
    - "python"
    - "javascript"
    - "programming"
    - "algorithm"
  - source_model: maywell/PiVoT-0.1-Starling-LM-RP
    positive_prompts:
    - "storywriting"
    - "write"
    - "scene"
    - "story"
    - "character"
  - source_model: WizardLM/WizardMath-7B-V1.1
    positive_prompts:
    - "reason"
    - "math"
    - "mathematics"
    - "solve"
    - "count"
tokenizer_source: union
```

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

from transformers import AutoTokenizer
import transformers
import torch

model = "mychen76/openmixtral-6x7b-v2"

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": "Why the sky is blue"}]
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__openmixtral-6x7b-v2)


|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |72.33|
|AI2 Reasoning Challenge (25-Shot)|68.52|
|HellaSwag (10-Shot)              |86.75|
|MMLU (5-Shot)                    |65.11|
|TruthfulQA (0-shot)              |65.13|
|Winogrande (5-shot)              |79.87|
|GSM8k (5-shot)                   |68.61|