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README.md

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+---
+license: other
+license_name: health-ai-developer-foundations
+license_link: https://developers.google.com/health-ai-developer-foundations/terms
+library_name: transformers
+pipeline_tag: image-text-to-text
+extra_gated_heading: Access MedGemma on Hugging Face
+extra_gated_prompt: To access MedGemma on Hugging Face, you're required to review
+  and agree to [Health AI Developer Foundation's terms of use](https://developers.google.com/health-ai-developer-foundations/terms).
+  To do this, please ensure you're logged in to Hugging Face and click below. Requests
+  are processed immediately.
+extra_gated_button_content: Acknowledge license
+base_model: google/medgemma-27b-text-it
+tags:
+- medical
+- clinical-reasoning
+- thinking
+- mlx
+- mlx-my-repo
+---
+
+# mlx-community/medgemma-27b-text-it-bf16
+
+The Model [mlx-community/medgemma-27b-text-it-bf16](https://huggingface.co/mlx-community/medgemma-27b-text-it-bf16) 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**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("mlx-community/medgemma-27b-text-it-bf16")
+
+prompt="hello"
+
+if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
+    messages = [{"role": "user", "content": prompt}]
+    prompt = tokenizer.apply_chat_template(
+        messages, tokenize=False, add_generation_prompt=True
+    )
+
+response = generate(model, tokenizer, prompt=prompt, verbose=True)
+```