AthuKawaleLogituit/Qwen2.5-Coder-3B-Fine-Tuned
AthuKawaleLogituit/Qwen2.5-Coder-3B-Fine-Tuned is a 3.1 billion parameter Qwen2.5-Coder model fine-tuned by AthuKawaleLogituit. This model was optimized for speed using Unsloth and Huggingface's TRL library, building upon the unsloth/Qwen2.5-Coder-3B-Instruct-bnb-4bit base. With a 32K context length, it is designed for efficient code-related tasks.
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Model Overview
AthuKawaleLogituit/Qwen2.5-Coder-3B-Fine-Tuned is a 3.1 billion parameter language model developed by AthuKawaleLogituit. It is fine-tuned from the unsloth/Qwen2.5-Coder-3B-Instruct-bnb-4bit base model, leveraging the Qwen2.5-Coder architecture. The model was specifically trained for enhanced efficiency and speed using the Unsloth library and Huggingface's TRL library, resulting in a 2x faster training process.
Key Capabilities
- Efficient Code-Related Tasks: Optimized for performance in coding scenarios due to its Coder base and fine-tuning.
- Fast Training: Benefits from Unsloth's optimizations, allowing for quicker iteration and deployment.
- 32K Context Length: Supports processing longer sequences of code or text, which is beneficial for complex programming tasks.
Good For
- Developers seeking a compact yet capable model for code generation, completion, or understanding.
- Applications requiring a balance of performance and resource efficiency for coding tasks.
- Experimentation with models fine-tuned using Unsloth for accelerated training.