--- language: - en license: apache-2.0 base_model: codellama/CodeLlama-7b-hf tags: - code - python - codellama - qlora - unsloth datasets: - custom pipeline_tag: text-generation --- # CodeLlama 7B Python AI Assistant (QLoRA) Fine-tuned CodeLlama-7B model specialized for Python programming assistance using QLoRA (Quantized Low-Rank Adaptation). ## Model Description - **Base Model:** [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) - **Fine-tuning Method:** QLoRA (4-bit quantization with LoRA adapters) - **Framework:** Unsloth + Transformers - **Training Data:** Custom Python programming examples ## Usage This repository contains **LoRA adapters only**. To use, merge the adapters with the base model. from unsloth import FastLanguageModel model, tokenizer = FastLanguageModel.from_pretrained( model_name="pranav-pvnn/codellama-7b-python-ai-assistant", max_seq_length=2048, load_in_4bit=True, ) prompt = "### Instruction:\nWrite a Python function to calculate factorial.\n### Response:\n" inputs = tokenizer(prompt, return_tensors="pt").to("cuda") outputs = model.generate(**inputs, max_new_tokens=256) print(tokenizer.decode(outputs, skip_special_tokens=True)) ## Training Details - **Quantization:** 4-bit - **LoRA Rank:** 64 - **Learning Rate:** 2e-4 - **Epochs:** 4 - **Max Seq Length:** 2048 - **GPU:** NVIDIA Tesla T4 ## Limitations - Requires base model for inference. - Optimized for Python code generation. - Trained on custom dataset (~2,000 examples). ## Citation @misc{codellama-7b-python-assistant, author = {pranav-pvnn}, title = {CodeLlama 7B Python AI Assistant}, year = {2025}, publisher = {HuggingFace}, howpublished = {\url{https://huggingface.co/pranav-pvnn/codellama-7b-python-ai-assistant}} } ## Acknowledgements - Base Model: [Meta's CodeLlama](https://huggingface.co/codellama/CodeLlama-7b-hf) - Training Framework: [Unsloth](https://github.com/unslothai/unsloth) - Quantization: [bitsandbytes](https://github.com/TimDettmers/bitsandbytes) - LoRA: [PEFT](https://github.com/huggingface/peft)