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--- |
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inference: false |
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datasets: |
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- medalpaca/medical_meadow_medqa |
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language: |
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- en |
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library_name: transformers |
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tags: |
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- biology |
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- medical |
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- QA |
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- healthcare |
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license: mit |
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--- |
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# Galen |
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Galen is fine-tuned from [Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2), using [medical quesion answering dataset](https://huggingface.co/datasets/medalpaca/medical_meadow_medqa) |
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### Galen's view about future of medicine and AI: |
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 |
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# Get Started |
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Install "accelerate" to use CUDA GPU |
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```bash |
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pip install accelerate |
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``` |
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```py |
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from transformers import AutoTokenizer, pipeline |
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``` |
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```py |
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tokenizer = AutoTokenizer.from_pretrained('ahmed-ai/galen') |
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model_pipeline = pipeline(task="text-generation", model='ahmed-ai/galen', tokenizer=tokenizer, max_length=256, temperature=0.5, top_p=0.6) |
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``` |
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```py |
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result = model_pipeline('What is squamous cell carcinoma') |
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#print the generated text |
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print(result[0]['generated_text'][len(prompt):]) |
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``` |
