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README.md

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-license: mit
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+
+# 🤖 Delta - Tiny Helpful Assistant (GPT2-style)
+
+Delta is a tiny transformer-based language model inspired by GPT-2, designed to be lightweight, fast, and helpful for simple natural language tasks.
+
+This project demonstrates how to train a minimal GPT-2-like model using Hugging Face Transformers on custom text, then serve it locally via a FastAPI API or deploy it to Hugging Face Hub.
+
+---
+
+## 🧠 Model Details
+
+- Architecture: GPT2 (custom config)
+- Parameters: ~4.7M
+- Layers: 2
+- Embedding Size: 128
+- Heads: 2
+- Max Sequence Length: 128
+- Trained on: ~300 characters (demo text)
+- Format: `PyTorch`, ready for GGUF/Ollama conversion
+
+---
+
+## 📁 Files Included
+
+- `config.json`: GPT2 model configuration
+- `pytorch_model.bin`: Fine-tuned model weights
+- `tokenizer_config.json`, `vocab.json`, `merges.txt`: Tokenizer files
+- `generation_config.json`: Optional generation tuning
+- `README.md`: You’re reading it!
+- `main.py`: (Optional) FastAPI local serving code
+
+---
+
+## 🚀 Quick Start (Hugging Face Transformers)
+
+Install dependencies:
+
+```bash
+pip install transformers torch
+```
+
+Load and use the model:
+
+```python
+from transformers import GPT2Tokenizer, GPT2LMHeadModel
+
+tokenizer = GPT2Tokenizer.from_pretrained("Vijay1303/delta")
+model = GPT2LMHeadModel.from_pretrained("Vijay1303/delta")
+model.eval()
+
+input_ids = tokenizer("Hello Delta, can you help me?", return_tensors="pt").input_ids
+outputs = model.generate(input_ids, max_length=50, do_sample=True)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+---
+
+## 🌐 Run Locally via FastAPI
+
+1. Install dependencies:
+```bash
+pip install fastapi uvicorn transformers torch
+```
+
+2. Run server:
+```bash
+uvicorn main:app --reload --port 8000
+```
+
+3. Query API:
+```bash
+curl -X POST http://localhost:8000/generate \
+  -H "Content-Type: application/json" \
+  -d '{"prompt": "Hello Delta,", "max_length": 50}'
+```
+
+---
+
+## 📦 Deployment
+
+You can:
+- Convert to GGUF for Ollama or llama.cpp
+- Push to Hugging Face Hub
+- Serve via an API (FastAPI, Flask, etc.)
+
+---
+
+## ⚠️ Limitations
+
+- Trained on a small dataset (~300 characters)
+- Not suitable for production tasks
+- For experimentation and educational use
+
+---
+
+## 📚 References
+
+- [Hugging Face Transformers](https://github.com/huggingface/transformers)
+- [Training GPT2 from Scratch](https://huggingface.co/blog/how-to-train)
+- [Ollama](https://ollama.com/)
+- [GGUF Format](https://github.com/ggerganov/llama.cpp)
+
+---
+
+## 👨‍💻 Author
+
+**Vijay1303**  
+[Hugging Face Profile](https://huggingface.co/Vijay1303)  
+Feel free to ⭐ the repo if you find this useful!