Update README.md

README.md

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----
-license: apache-2.0
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+---
+license: mit
+datasets:
+- HuggingFaceH4/CodeAlpaca_20K
+base_model:
+- Qwen/Qwen3-0.6B
+---
+# 🧠 Qwen-0.6B – Code Generation Model
+
+**Model Repo:** `XformAI-india/qwen-0.6b-coder`  
+**Base Model:** [`Qwen/Qwen-0.5B`](https://huggingface.co/Qwen/Qwen-0.5B)  
+**Task:** Code generation and completion  
+**Trained by:** [XformAI](https://xformai.in)  
+**Date:** May 2025
+
+---
+
+## 🔍 What is this?
+
+This is a fine-tuned version of Qwen-0.6B optimized for **code generation, completion, and programming logic reasoning**.
+
+It’s designed to be lightweight, fast, and capable of handling common developer tasks across multiple programming languages.
+
+---
+
+## 💻 Use Cases
+
+- AI-powered code assistants  
+- Auto-completion for IDEs  
+- Offline code generation  
+- Learning & training environments  
+- Natural language → code prompts
+
+---
+
+## 📚 Training Details
+
+| Parameter     | Value        |
+|---------------|--------------|
+| Epochs        | 3            |
+| Batch Size    | 16           |
+| Optimizer     | AdamW        |
+| Precision     | bfloat16     |
+| Context Window | 2048 tokens |
+| Framework     | 🤗 Transformers + LoRA (PEFT)
+
+---
+
+## 🚀 Example Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("XformAI-india/qwen-0.6b-coder")
+tokenizer = AutoTokenizer.from_pretrained("XformAI-india/qwen-0.6b-coder")
+
+prompt = "Write a Python function that checks if a number is prime:"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=150)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))