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README.md

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+# CodeLlama Fine-Tuning for RTL Code Generation
+
+This repository contains scripts, datasets, and documentation for fine-tuning CodeLlama-7B-Instruct model for Verilog/SystemVerilog RTL code generation.
+
+## 📋 Overview
+
+This project fine-tunes CodeLlama-7B-Instruct to generate synthesizable Verilog/SystemVerilog code for hardware design tasks, specifically focusing on FIFO implementations.
+
+## 🎯 Features
+
+- **CodeLlama-7B-Instruct Fine-tuning** with LoRA
+- **Chat Template Format** support
+- **Dataset Processing** and validation scripts
+- **Training Scripts** with checkpoint resume capability
+- **Inference Scripts** for testing fine-tuned models
+- **Comprehensive Documentation** and guides
+
+## 📁 Repository Structure
+
+```
+codellama-migration/
+├── datasets/                    # Training datasets
+│   ├── raw/                    # Original datasets
+│   └── processed/              # Processed and formatted datasets
+│       ├── split/              # Train/val/test splits (original format)
+│       └── split_chat_format/  # Train/val/test splits (chat format)
+├── scripts/
+│   ├── training/               # Training scripts
+│   ├── inference/              # Inference scripts
+│   └── dataset_split.py        # Dataset splitting utility
+├── Documentation/              # All .md documentation files
+└── Scripts/                    # Utility scripts
+```
+
+## 🚀 Quick Start
+
+### Prerequisites
+
+- Python 3.8+
+- CUDA-capable GPU (recommended)
+- HuggingFace transformers library
+- PyTorch
+
+### Installation
+
+```bash
+pip install transformers torch peft accelerate bitsandbytes
+```
+
+### Training
+
+```bash
+bash start_training_chat_format.sh
+```
+
+### Inference
+
+```bash
+python3 scripts/inference/inference_codellama.py \
+    --mode local \
+    --model-path training-outputs/codellama-fifo-v2-chat \
+    --base-model-path models/base-models/CodeLlama-7B-Instruct \
+    --prompt "Your prompt here"
+```
+
+## 📊 Dataset
+
+The dataset contains 94 samples of FIFO implementations in Verilog format. It's split into:
+- Training: 70 samples (75%)
+- Validation: 9 samples (10%)
+- Test: 15 samples (15%)
+
+## 📚 Documentation
+
+- **MIGRATION_PROGRESS.md** - Overall migration tracking
+- **TRAINING_COMPLETE.md** - Training completion details
+- **COMPARISON_REPORT.md** - Expected vs Generated comparison
+- **FILE_INVENTORY.md** - Complete file listing
+
+## 🤖 Model Information
+
+**Base Model**: CodeLlama-7B-Instruct  
+**Fine-tuning Method**: LoRA (Low-Rank Adaptation)  
+**LoRA Rank**: 48  
+**LoRA Alpha**: 96  
+**Trainable Parameters**: ~120M (3.31% of total)
+
+## 📝 License
+
+This project is for internal use by Elinnos Systems Pvt Limited.
+
+## 👥 Contributors
+
+Elinnos Systems Pvt Limited
+
+## 🔗 Links
+
+- Organization: https://huggingface.co/Elinnos
+- Base Model: https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf
+
+---
+
+**Note**: Model weights are not included in this repository. Fine-tuned models are stored separately.
+