Issactoto/qwen2.5-1.5b-sft-python-merged
Issactoto/qwen2.5-1.5b-sft-python-merged is a 1.5 billion parameter language model based on the Qwen2.5 architecture, fine-tuned for Python code generation. This model demonstrates a pass@1 score of 0.2439 on code tasks, indicating its capability in generating correct Python code. With a context length of 32768 tokens, it is suitable for applications requiring Python code completion and generation.
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Model Overview
Issactoto/qwen2.5-1.5b-sft-python-merged is a specialized language model built upon the Qwen2.5 architecture, featuring 1.5 billion parameters. It has undergone supervised fine-tuning (SFT) specifically for Python programming tasks, making it adept at understanding and generating Python code.
Key Capabilities
- Python Code Generation: The model is fine-tuned to produce Python code, as evidenced by its performance on coding benchmarks.
- Code Completion: Its training focuses on generating functional and syntactically correct Python snippets.
- Context Handling: With a substantial context window of 32768 tokens, it can process and generate code within larger programming contexts.
Performance
This model achieves a pass@1 score of 0.2439 on relevant code generation benchmarks. This metric indicates its ability to generate a correct solution on the first attempt, highlighting its utility for developers seeking assistance with Python coding.
Good For
- Automated Python Scripting: Generating small to medium-sized Python functions or scripts.
- Developer Tools: Integrating into IDEs for intelligent code completion and suggestion.
- Educational Purposes: Assisting learners with Python programming exercises and examples.