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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