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README.md

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+---
+datasets:
+- TeichAI/claude-4.5-opus-high-reasoning-250x
+base_model: leonsarmiento/Qwen3-8B-Claude-4.5-Opus-High-Reasoning-Distill-4bit-mlx
+pipeline_tag: text-generation
+library_name: mlx
+tags:
+- mlx
+- mlx
+- mlx-my-repo
+---
+
+# introvoyz041/Qwen3-8B-Claude-4.5-Opus-High-Reasoning-Distill-4bit-mlx-mlx-8Bit
+
+The Model [introvoyz041/Qwen3-8B-Claude-4.5-Opus-High-Reasoning-Distill-4bit-mlx-mlx-8Bit](https://huggingface.co/introvoyz041/Qwen3-8B-Claude-4.5-Opus-High-Reasoning-Distill-4bit-mlx-mlx-8Bit) was converted to MLX format from [leonsarmiento/Qwen3-8B-Claude-4.5-Opus-High-Reasoning-Distill-4bit-mlx](https://huggingface.co/leonsarmiento/Qwen3-8B-Claude-4.5-Opus-High-Reasoning-Distill-4bit-mlx) 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/Qwen3-8B-Claude-4.5-Opus-High-Reasoning-Distill-4bit-mlx-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)
+```