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README.md

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+---
+language:
+- en
+- fr
+- de
+- es
+- pt
+- it
+- ja
+- ko
+- ru
+- zh
+- ar
+- fa
+- id
+- ms
+- ne
+- pl
+- ro
+- sr
+- sv
+- tr
+- uk
+- vi
+- hi
+- bn
+license: apache-2.0
+library_name: vllm
+inference: false
+base_model: lmstudio-community/Devstral-Small-2507-MLX-4bit
+extra_gated_description: If you want to learn more about how we process your personal
+  data, please read our <a href="https://mistral.ai/terms/">Privacy Policy</a>.
+pipeline_tag: text2text-generation
+tags:
+- mlx
+- mlx
+- mlx-my-repo
+---
+
+# introvoyz041/Devstral-Small-2507-MLX-4bit-mlx-4Bit
+
+The Model [introvoyz041/Devstral-Small-2507-MLX-4bit-mlx-4Bit](https://huggingface.co/introvoyz041/Devstral-Small-2507-MLX-4bit-mlx-4Bit) was converted to MLX format from [lmstudio-community/Devstral-Small-2507-MLX-4bit](https://huggingface.co/lmstudio-community/Devstral-Small-2507-MLX-4bit) using mlx-lm version **0.28.3**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("introvoyz041/Devstral-Small-2507-MLX-4bit-mlx-4Bit")
+
+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)
+```