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README.md

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+---
+library_name: transformers
+license: gemma
+license_link: https://ai.google.dev/gemma/terms
+pipeline_tag: text-generation
+extra_gated_heading: Access CodeGemma on Hugging Face
+extra_gated_prompt: To access CodeGemma on Hugging Face, you’re required to review
+  and agree to Google’s usage license. 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
+widget:
+- text: '<start_of_turn>user Write a Python function to calculate the nth fibonacci
+    number.<end_of_turn> <start_of_turn>model
+
+    '
+inference:
+  parameters:
+    max_new_tokens: 200
+tags:
+- mlx
+base_model: google/codegemma-1.1-7b-it
+---
+
+# mlx-community/codegemma-1.1-7b-it-6bit
+
+The Model [mlx-community/codegemma-1.1-7b-it-6bit](https://huggingface.co/mlx-community/codegemma-1.1-7b-it-6bit) was converted to MLX format from [google/codegemma-1.1-7b-it](https://huggingface.co/google/codegemma-1.1-7b-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/codegemma-1.1-7b-it-6bit")
+
+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)
+```