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README.md

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+---
+license: apache-2.0
+license_link: https://huggingface.co/huihui-ai/Qwen2.5-Coder-32B-Instruct-abliterate/blob/main/LICENSE
+language:
+- en
+base_model: huihui-ai/Qwen2.5-Coder-32B-Instruct-abliterated
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- code
+- codeqwen
+- chat
+- qwen
+- qwen-coder
+- abliterated
+- uncensored
+- mlx
+- mlx-my-repo
+---
+
+# Felladrin/Qwen2.5-Coder-32B-Instruct-abliterated-Q4-mlx
+
+The Model [Felladrin/Qwen2.5-Coder-32B-Instruct-abliterated-Q4-mlx](https://huggingface.co/Felladrin/Qwen2.5-Coder-32B-Instruct-abliterated-Q4-mlx) was converted to MLX format from [huihui-ai/Qwen2.5-Coder-32B-Instruct-abliterated](https://huggingface.co/huihui-ai/Qwen2.5-Coder-32B-Instruct-abliterated) using mlx-lm version **0.20.5**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("Felladrin/Qwen2.5-Coder-32B-Instruct-abliterated-Q4-mlx")
+
+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)
+```