Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,42 @@
+---
+base_model: AlejandroOlmedo/DeepSeek-R1-Distill-Qwen-7B-GRPO_Math-8bit-mlx
+datasets: DigitalLearningGmbH/MATH-lighteval
+library_name: transformers
+model_name: DeepSeek-R1-Distill-Qwen-7B-GRPO_Math
+tags:
+- generated_from_trainer
+- open-r1
+- trl
+- grpo
+- mlx
+- mlx-my-repo
+- mlx
+- mlx-my-repo
+licence: license
+---
+
+# introvoyz041/DeepSeek-R1-Distill-Qwen-7B-GRPO_Math-8bit-mlx-mlx-4Bit
+
+The Model [introvoyz041/DeepSeek-R1-Distill-Qwen-7B-GRPO_Math-8bit-mlx-mlx-4Bit](https://huggingface.co/introvoyz041/DeepSeek-R1-Distill-Qwen-7B-GRPO_Math-8bit-mlx-mlx-4Bit) was converted to MLX format from [AlejandroOlmedo/DeepSeek-R1-Distill-Qwen-7B-GRPO_Math-8bit-mlx](https://huggingface.co/AlejandroOlmedo/DeepSeek-R1-Distill-Qwen-7B-GRPO_Math-8bit-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/DeepSeek-R1-Distill-Qwen-7B-GRPO_Math-8bit-mlx-mlx-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)
+```