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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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language: en |
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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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tags: |
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- medical |
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- x-ray |
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- pathology |
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- dermatology |
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- fundus |
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- radiology report generation |
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- chest-x-ray |
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- medical-embeddings |
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- image-classification |
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- zero-shot-image-classification |
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- image-feature-extraction |
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- image-text-to-text |
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- mlx |
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base_model: google/gemma-3-27b-pt |
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--- |
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# mlx-community/medgemma-27b-it-8bit |
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This model was converted to MLX format from [`google/medgemma-27b-it`]() using mlx-vlm version **0.3.0**. |
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Refer to the [original model card](https://huggingface.co/google/medgemma-27b-it) for more details on the model. |
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## Use with mlx |
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```bash |
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pip install -U mlx-vlm |
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``` |
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```bash |
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python -m mlx_vlm.generate --model mlx-community/medgemma-27b-it-8bit --max-tokens 100 --temperature 0.0 --prompt "Describe this image." --image <path_to_image> |
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``` |
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