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--- |
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license: apache-2.0 |
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tags: |
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- moe |
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- merge |
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- epfl-llm/meditron-7b |
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- microsoft/Orca-2-7b |
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--- |
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# Medorca-2x7b |
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Medorca-2x7b is a Mixure of Experts (MoE) made with the following models: |
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* [epfl-llm/meditron-7b](https://huggingface.co/epfl-llm/meditron-7b) |
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* [microsoft/Orca-2-7b](https://huggingface.co/microsoft/Orca-2-7b) |
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## Evaluations |
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| Benchmark | Medorca-2x7b | Orca-2-7b | llama-2-7b | meditron-7b | meditron-70b | |
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| --- | --- | --- | --- | --- | --- | |
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| MedMCQA | | | | | | |
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| ClosedPubMedQA | | | | | | |
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| PubMedQA | | | | | | |
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| MedQA | | | | | | |
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| MedQA4 | | | | | | |
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| MedicationQA | | | | | | |
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| MMLU Medical | | | | | | |
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| MMLU | 53.3 | **56.37** | | | | |
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| TruthfulQA | 48.04 | **52.45** | | | | |
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| GSM8K | **20.64** | 14.71 | | | | |
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| ARC | 54.1 | 54.1 | | | | |
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| HellaSwag | 76.04 | **76.19** | | | | |
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| Winogrande | **74.51** | 73.48 | | | | |
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More details on the Open LLM Leaderboard evaluation results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Technoculture__Medorca-2x7b.) |
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## 🧩 Configuration |
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```yaml |
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base_model: microsoft/Orca-2-7b |
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gate_mode: hidden |
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dtype: bfloat16 |
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experts: |
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- source_model: epfl-llm/meditron-7b |
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positive_prompts: |
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- "How does sleep affect cardiovascular health?" |
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- "Could a plant-based diet improve arthritis symptoms?" |
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- "A patient comes in with symptoms of dizziness and nausea..." |
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- "When discussing diabetes management, the key factors to consider are..." |
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- "The differential diagnosis for a headache with visual aura could include..." |
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negative_prompts: |
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- "Recommend a good recipe for a vegetarian lasagna." |
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- "Give an overview of the French Revolution." |
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- "Explain how a digital camera captures an image." |
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- "What are the environmental impacts of deforestation?" |
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- "The recent advancements in artificial intelligence have led to developments in..." |
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- "The fundamental concepts in economics include ideas like supply and demand, which explain..." |
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- source_model: microsoft/Orca-2-7b |
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positive_prompts: |
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- "Here is a funny joke for you -" |
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- "When considering the ethical implications of artificial intelligence, one must take into account..." |
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- "In strategic planning, a company must analyze its strengths and weaknesses, which involves..." |
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- "Understanding consumer behavior in marketing requires considering factors like..." |
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- "The debate on climate change solutions hinges on arguments that..." |
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negative_prompts: |
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- "In discussing dietary adjustments for managing hypertension, it's crucial to emphasize..." |
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- "For early detection of melanoma, dermatologists recommend that patients regularly check their skin for..." |
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- "Explaining the importance of vaccination, a healthcare professional should highlight..." |
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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 = "Technoculture/Medorca-2x7b" |
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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}, |
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) |
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messages = [{"role": "user", "content": "Why am i feeling so tired this month?"}] |
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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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``` |
