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README.md

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+---
+license: apache-2.0
+language:
+- en
+base_model: alamios/DeepSeek-R1-DRAFT-Qwen2.5-Coder-0.5B
+datasets:
+- alamios/DeepSeek-R1-Distill-Qwen-32B-Conversations
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- code
+- qwen
+- qwen2.5
+- qwen-coder
+- codeqwen
+- deepseek
+- mlx
+- mlx-my-repo
+---
+
+# jmfirth/DeepSeek-R1-DRAFT-Qwen2.5-Coder-0.5B-mlx-8Bit
+
+The Model [jmfirth/DeepSeek-R1-DRAFT-Qwen2.5-Coder-0.5B-mlx-8Bit](https://huggingface.co/jmfirth/DeepSeek-R1-DRAFT-Qwen2.5-Coder-0.5B-mlx-8Bit) was converted to MLX format from [alamios/DeepSeek-R1-DRAFT-Qwen2.5-Coder-0.5B](https://huggingface.co/alamios/DeepSeek-R1-DRAFT-Qwen2.5-Coder-0.5B) using mlx-lm version **0.22.1**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("jmfirth/DeepSeek-R1-DRAFT-Qwen2.5-Coder-0.5B-mlx-8Bit")
+
+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)
+```