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README.md

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+---
+language:
+- en
+- fr
+- de
+- es
+- it
+- pt
+- zh
+- ja
+- ru
+- ko
+license: apache-2.0
+library_name: vllm
+inference: false
+base_model: huihui-ai/Mistral-Small-24B-Instruct-2501-abliterated
+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>.
+tags:
+- abliterated
+- uncensored
+- transformers
+- mlx
+- mlx-my-repo
+---
+
+# KYUNGYONG/Mistral-Small-24B-Instruct-2501-abliterated-4bit
+
+The Model [KYUNGYONG/Mistral-Small-24B-Instruct-2501-abliterated-4bit](https://huggingface.co/KYUNGYONG/Mistral-Small-24B-Instruct-2501-abliterated-4bit) was converted to MLX format from [huihui-ai/Mistral-Small-24B-Instruct-2501-abliterated](https://huggingface.co/huihui-ai/Mistral-Small-24B-Instruct-2501-abliterated) using mlx-lm version **0.21.5**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("KYUNGYONG/Mistral-Small-24B-Instruct-2501-abliterated-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)
+```