imjosephk/Qwen2.5-Luau-Coder-3B
imjosephk/Qwen2.5-Luau-Coder-3B is a 3.1 billion parameter Qwen2.5-Coder model developed by imjosephk, fine-tuned from unsloth/Qwen2.5-Coder-3B-Instruct-bnb-4bit. This model is optimized for code generation and related tasks, leveraging a 32768 token context length. It was trained using Unsloth and Huggingface's TRL library, emphasizing efficient fine-tuning.
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Model Overview
imjosephk/Qwen2.5-Luau-Coder-3B is a 3.1 billion parameter language model based on the Qwen2.5-Coder architecture. Developed by imjosephk, this model was fine-tuned from unsloth/Qwen2.5-Coder-3B-Instruct-bnb-4bit with a focus on code-related applications. It supports a substantial context length of 32768 tokens, making it suitable for handling larger codebases or complex programming prompts.
Key Capabilities
- Code Generation: Optimized for generating programming code across various languages.
- Efficient Fine-tuning: The model was fine-tuned using Unsloth and Huggingface's TRL library, indicating an emphasis on faster and more resource-efficient training processes.
- Qwen2.5-Coder Base: Benefits from the robust capabilities of the Qwen2.5-Coder family, known for its performance in coding tasks.
Good For
- Code Completion: Assisting developers with completing code snippets.
- Code Generation Tasks: Creating new code based on natural language descriptions.
- Educational Purposes: Learning and experimenting with efficient fine-tuning techniques for large language models.