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README.md

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+---
+license: llama3.1
+language:
+- en
+inference: false
+fine-tuning: false
+tags:
+- nvidia
+- llama3.1
+- reward model
+- mlx
+- mlx-my-repo
+datasets:
+- nvidia/HelpSteer2
+base_model: nvidia/Llama-3.1-Nemotron-70B-Reward-HF
+---
+
+# cnfusion/Llama-3.1-Nemotron-70B-Reward-HF-Q2-mlx
+
+The Model [cnfusion/Llama-3.1-Nemotron-70B-Reward-HF-Q2-mlx](https://huggingface.co/cnfusion/Llama-3.1-Nemotron-70B-Reward-HF-Q2-mlx) was converted to MLX format from [nvidia/Llama-3.1-Nemotron-70B-Reward-HF](https://huggingface.co/nvidia/Llama-3.1-Nemotron-70B-Reward-HF) using mlx-lm version **0.19.2**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("cnfusion/Llama-3.1-Nemotron-70B-Reward-HF-Q2-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)
+```