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README.md

@@ -9,6 +9,7 @@ tags:
   - reasoning
   - 3b
   - menda
+  - chat
 datasets:
   - custom
 model-index:
@@ -67,6 +68,40 @@ Menda-3b-750 is a fine-tuned version of Qwen2.5-3B-Instruct, trained with GRPO (
 - **Training Steps**: 750
 - **Context Length**: 4096 tokens
 - **Parameters**: 3 billion
+- **Chat Template**: Uses the Qwen2 chat template
+
+## Chat Format
+
+This model uses the standard Qwen2 chat template. For best results when using the model directly, format your prompts as follows:
+
+```
+<|im_start|>system
+You are a helpful AI assistant.<|im_end|>
+<|im_start|>user
+Your question here<|im_end|>
+<|im_start|>assistant
+```
+
+When using the model through the Hugging Face Transformers library, the chat template will be applied automatically when using the `chat_template` functionality:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "weathermanj/Menda-3b-750"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+messages = [
+    {"role": "system", "content": "You are a helpful AI assistant."},
+    {"role": "user", "content": "Explain the concept of machine learning in simple terms."}
+]
+
+prompt = tokenizer.apply_chat_template(messages, tokenize=False)
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_length=300)
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(response)
+```
 
 ## Benchmark Results