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--- |
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license: apache-2.0 |
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tags: |
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- merge |
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--- |
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# openmixtral-6x7b-v2 |
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Quantized openmixtral-6x7b-merged_v2 is a merge of the following 6x7B models: |
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## 🧩 Configuration |
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```yaml |
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base_model: mlabonne/Marcoro14-7B-slerp |
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experts: |
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- source_model: openchat/openchat-3.5-1210 |
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positive_prompts: |
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- "chat" |
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- "assistant" |
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- "tell me" |
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- "explain" |
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- source_model: Weyaxi/Einstein-v4-7B |
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positive_prompts: |
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- "physics" |
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- "biology" |
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- "chemistry" |
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- "science" |
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- source_model: BioMistral/BioMistral-7B |
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positive_prompts: |
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- "medical" |
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- "pubmed" |
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- "healthcare" |
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- "health" |
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- source_model: beowolx/CodeNinja-1.0-OpenChat-7B |
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positive_prompts: |
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- "code" |
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- "python" |
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- "javascript" |
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- "programming" |
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- "algorithm" |
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- source_model: maywell/PiVoT-0.1-Starling-LM-RP |
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positive_prompts: |
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- "storywriting" |
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- "write" |
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- "scene" |
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- "story" |
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- "character" |
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- source_model: WizardLM/WizardMath-7B-V1.1 |
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positive_prompts: |
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- "reason" |
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- "math" |
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- "mathematics" |
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- "solve" |
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- "count" |
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tokenizer_source: union |
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``` |
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## 💻 Usage |
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```python |
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!pip install -qU transformers bitsandbytes accelerate |
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from transformers import AutoTokenizer |
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import transformers |
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import torch |
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model = "mychen76/openmixtral-6x7b-v2" |
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tokenizer = AutoTokenizer.from_pretrained(model) |
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pipeline = transformers.pipeline( |
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"text-generation", |
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model=model, |
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model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True}, |
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) |
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messages = [{"role": "user", "content": "Why the sky is blue"}] |
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prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95) |
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print(outputs[0]["generated_text"]) |
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``` |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_mychen76__openmixtral-6x7b-v2) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |72.33| |
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|AI2 Reasoning Challenge (25-Shot)|68.52| |
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|HellaSwag (10-Shot) |86.75| |
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|MMLU (5-Shot) |65.11| |
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|TruthfulQA (0-shot) |65.13| |
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|Winogrande (5-shot) |79.87| |
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|GSM8k (5-shot) |68.61| |
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