joomhadi/ft-model-joomha-base-qwen2.5-coder-3b
The joomhadi/ft-model-joomha-base-qwen2.5-coder-3b is a 3.1 billion parameter Qwen2.5-Coder-3B-Instruct model, developed by joomhadi and fine-tuned for coding tasks. This model was optimized for faster training using Unsloth and Huggingface's TRL library, making it efficient for code generation and related applications. It features a 32768 token context length, suitable for handling substantial code snippets and complex programming instructions.
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Model Overview
The joomhadi/ft-model-joomha-base-qwen2.5-coder-3b is a 3.1 billion parameter language model, fine-tuned by joomhadi. It is based on the Qwen2.5-Coder-3B-Instruct architecture and is specifically designed for coding-related tasks. This model leverages a substantial 32768 token context length, enabling it to process and generate extensive code segments.
Key Capabilities
- Code Generation: Optimized for generating programming code across various languages.
- Efficient Training: Fine-tuned using Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.
- Large Context Window: Supports a 32768 token context, beneficial for understanding and completing complex coding projects or multi-file programming tasks.
Good For
- Developers requiring a compact yet capable model for code completion and generation.
- Applications that benefit from efficient, fine-tuned models for programming tasks.
- Scenarios where a large context window is crucial for handling extensive codebases or detailed instructions.