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--- |
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license: other |
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license_name: health-ai-developer-foundations |
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license_link: https://developers.google.com/health-ai-developer-foundations/terms |
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library_name: transformers |
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pipeline_tag: image-text-to-text |
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extra_gated_heading: Access MedGemma on Hugging Face |
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extra_gated_prompt: To access MedGemma on Hugging Face, you're required to review |
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and agree to [Health AI Developer Foundation's terms of use](https://developers.google.com/health-ai-developer-foundations/terms). |
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To do this, please ensure you're logged in to Hugging Face and click below. Requests |
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are processed immediately. |
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extra_gated_button_content: Acknowledge license |
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base_model: google/medgemma-27b-text-it |
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tags: |
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- medical |
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- clinical-reasoning |
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- thinking |
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- mlx |
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- mlx-my-repo |
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--- |
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# mlx-community/medgemma-27b-text-it-8bit |
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The Model [mlx-community/medgemma-27b-text-it-8bit](https://huggingface.co/mlx-community/medgemma-27b-text-it-8bit) was converted to MLX format from [google/medgemma-27b-text-it](https://huggingface.co/google/medgemma-27b-text-it) using mlx-lm version **0.24.1**. |
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## Use with mlx |
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```bash |
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pip install mlx-lm |
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``` |
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```python |
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from mlx_lm import load, generate |
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model, tokenizer = load("mlx-community/medgemma-27b-text-it-8bit") |
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prompt="hello" |
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if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None: |
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messages = [{"role": "user", "content": prompt}] |
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prompt = tokenizer.apply_chat_template( |
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messages, tokenize=False, add_generation_prompt=True |
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) |
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response = generate(model, tokenizer, prompt=prompt, verbose=True) |
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``` |
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