AhmedSSoliman/Llama2-CodeGen-PEFT-QLoRA
AhmedSSoliman/Llama2-CodeGen-PEFT-QLoRA is a 7 billion parameter Llama 2 model fine-tuned by AhmedSSoliman on the CodeSearchNet dataset. Utilizing QLoRA and PEFT methods, this model is specifically optimized for code generation tasks. It leverages the Llama 2 architecture to provide a coding assistant capable of resolving programming instructions.
Loading preview...
Overview
AhmedSSoliman/Llama2-CodeGen-PEFT-QLoRA is a specialized 7 billion parameter language model built upon the Llama 2 architecture. It has been fine-tuned using the QLoRA method in conjunction with the PEFT library on the comprehensive CodeSearchNet dataset. This targeted training process enhances its capabilities specifically for code-related tasks, making it a dedicated coding assistant.
Key Capabilities
- Code Generation: Excels at generating code based on given instructions.
- Instruction Following: Designed to resolve programming instructions effectively.
- Efficient Fine-tuning: Leverages QLoRA for efficient fine-tuning of large models.
Good For
- Developers seeking an AI assistant for generating code snippets.
- Automating routine coding tasks.
- Educational purposes to understand code generation from natural language prompts.