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CodeWeave-QwenCoder
A fine-tuned code generation model optimized for Python and JavaScript development tasks.
Model Description
CodeWeave-QwenCoder is a specialized code generation model fine-tuned from Qwen/Qwen2.5-Coder-7B-Instruct for enhanced performance on real-world coding tasks.
Base Model
- Foundation: Qwen2.5-Coder-7B-Instruct from Alibaba's Qwen team
- Architecture: Transformer-based decoder-only model
- Parameters: 7B
Training Data
The model was fine-tuned on our curated CodeWeave-Instructions dataset, which includes:
- 50K Python programming exercises
- 30K JavaScript development tasks
- Code review and refactoring examples
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("toolevalxm/CodeWeave-QwenCoder")
tokenizer = AutoTokenizer.from_pretrained("toolevalxm/CodeWeave-QwenCoder")
Evaluation Results
| Benchmark | Score |
|---|---|
| HumanEval | 72.5% |
| MBPP | 68.3% |
Acknowledgements
We thank the Qwen team for the excellent base model.
License
The license for this model is apache-2.0.
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