anilkay/csharp-clean-code-qwen-lora-merged
The anilkay/csharp-clean-code-qwen-lora-merged model is a 7.6 billion parameter Qwen2.5-based language model developed by anilkay, fine-tuned for C# clean code generation. Utilizing Unsloth and Huggingface's TRL library, this model was trained for enhanced efficiency. It specializes in generating clean and optimized C# code, leveraging its 32768 token context length for complex programming tasks.
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Model Overview
The anilkay/csharp-clean-code-qwen-lora-merged is a 7.6 billion parameter language model developed by anilkay. It is based on the Qwen2.5 architecture and has been specifically fine-tuned for generating clean C# code. The model leverages a 32768 token context length, making it suitable for handling substantial code snippets and complex programming logic.
Key Characteristics
- Base Model: Fine-tuned from
unsloth/Qwen2.5-7B-bnb-4bit. - Training Efficiency: Training was accelerated using Unsloth and Huggingface's TRL library, resulting in a 2x faster training process.
- Specialization: Optimized for generating clean and idiomatic C# code.
Use Cases
This model is particularly well-suited for developers and teams working with C# who require assistance in:
- Generating C# code that adheres to clean code principles.
- Refactoring existing C# code for improved readability and maintainability.
- Automating the creation of C# code snippets or functions with a focus on best practices.