Update README.md

README.md

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----
-license: mit
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+---
+license: mit
+---
+
+# 🧠 AlphaMed
+
+This is the official model checkpoint for the paper:  
+**[AlphaMed: Incentivizing Medical Reasoning with minimalist Rule-Based RL](https://www.arxiv.org/abs/2505.17952)**  
+AlphaMed is a medical large language model trained **without supervised fine-tuning on chain-of-thought (CoT) data**, 
+relying solely on reinforcement learning to elicit step-by-step reasoning in complex medical tasks.
+
+## 🚀 Usage
+
+To use the model, format your input prompt as:
+
+> **Question:** [your medical question here]  
+> **Please reason step by step, and put the final answer in \boxed{}**
+
+### 🔬 Example
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+
+# Load model and tokenizer
+model_id = "che111/AlphaMed-3B-instruct-rl"  # Replace with actual repo path
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
+
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+# Format question
+prompt = (
+    "Question: A 45-year-old patient presents with chest pain radiating to the left arm and elevated troponin levels. "
+    "What is the most likely diagnosis?\n"
+    "Please reason step by step, and put the final answer in \\boxed{}"
+)
+
+# Generate output
+max_new_tokens=8196
+output = pipe(prompt, max_new_tokens=max_new_tokens, do_sample=False)[0]["generated_text"]
+print(output)