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