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README.md

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+---
+license: llama2
+base_model: codellama/CodeLlama-7b-hf
+tags:
+- code
+- llama
+- gguf
+- merged
+- python
+---
+
+# CodeLlama 7B Python AI Assistant (Merged GGUF)
+
+This is a merged version of the QLoRA fine-tuned CodeLlama-7B model. The LoRA weights have been merged with the base model and converted to GGUF format for easy deployment.
+
+## Model Details
+
+- **Base Model**: CodeLlama-7b-hf
+- **Original LoRA Adapter**: pranav-pvnn/codellama-7b-python-ai-assistant
+- **Fine-tuning Method**: QLoRA (4-bit quantization with LoRA)
+- **Format**: GGUF (self-contained, no separate adapter needed)
+- **Training Framework**: Unsloth
+
+## Available Quantizations
+
+- `codellama-7b-merged-f16.gguf` - Full precision (FP16) - ~13 GB
+- `codellama-7b-merged-Q4_K_M.gguf` - 4-bit quantization (recommended) - ~4 GB
+- `codellama-7b-merged-Q5_K_M.gguf` - 5-bit quantization (higher quality) - ~5 GB
+- `codellama-7b-merged-Q8_0.gguf` - 8-bit quantization (highest quality) - ~7 GB
+
+## Usage
+
+### With llama.cpp:
+```bash
+./llama-cli -m codellama-7b-merged-Q4_K_M.gguf -p "### Instruction:\nWrite a Python function to calculate factorial.\n### Response:\n"
+```
+
+### With Python (llama-cpp-python):
+```python
+from llama_cpp import Llama
+
+llm = Llama(model_path="codellama-7b-merged-Q4_K_M.gguf")
+prompt = "### Instruction:\nWrite a Python function to calculate factorial.\n### Response:\n"
+output = llm(prompt, max_tokens=256)
+print(output['choices'][0]['text'])
+```
+
+### With Ollama:
+1. Create a Modelfile:
+```
+FROM ./codellama-7b-merged-Q4_K_M.gguf
+```
+
+2. Create the model:
+```bash
+ollama create my-codellama -f Modelfile
+ollama run my-codellama "Write a Python function to sort a list"
+```
+
+## Training Details
+
+- **Quantization**: 4-bit QLoRA
+- **LoRA Rank**: 64
+- **Learning Rate**: 2e-4
+- **Epochs**: 4
+- **Max Seq Length**: 2048
+- **Training Data**: Custom Python programming examples (~2,000 examples)
+- **GPU**: NVIDIA Tesla T4
+
+## Prompt Format
+
+```
+### Instruction:
+[Your instruction here]
+### Response:
+```
+
+## License
+
+Same as base model (Llama 2 license)
+
+## Acknowledgements
+
+- Base Model: [Meta's CodeLlama](https://huggingface.co/codellama/CodeLlama-7b-hf)
+- Training Framework: [Unsloth](https://github.com/unslothai/unsloth)