Training Data
This model was trained on a dataset of curated C/C++ code from multiple licenses (GPL-2.0, Apache-2.0, MIT, public domain, and some source-available licenses, etc.). The original authors are not affiliated with or responsible for this model.
Base Model
Base model: Qwen/Qwen3-4B-Base
Fine-tuning Method
- Adapter: QLoRA
- Method: CPT
- Precision: trained with 4-bit base weights + BF16 compute, then merged to safetensors
Training Details
- Training time: ~74 hours
- Hardware: 1x NVIDIA RTX 5060 Ti
Notes
- This is an L0 base model, it is not instruction-tuned and may be more verbose with strict formatting request compared to an instruct model.
- Recommended usage is raw code continuation, or pairing with an external template strategy.
Intended use
- Code generation for C/C++
- Fast code completion
- Examples and prototyping
Constraints
- May produce incorrect code
- May reproduce identifiable upstream code fragments (including license headers) when prompted.
- Verify outputs, especially for memory safety and security-sensitive code.
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