Instructions to use code2lora/code2lora-direct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use code2lora/code2lora-direct with PEFT:
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- Notebooks
- Google Colab
- Kaggle
Code2LoRA โ direct-projection hypernetwork
Final checkpoint of the direct-projection Code2LoRA hypernetwork used in
the paper. Maps a repository-level embedding into a rank-16 LoRA adapter for
Qwen/Qwen2.5-Coder-1.5B in a single forward pass.
Files
| File | Description |
|---|---|
code2lora_direct.pt |
Trained Code2LoRAHead weights (~2.7 GB, fp32). Loaded with torch.load(map_location="cpu"). |
Training recipe
- 3 epochs on the
code2lora/code2lora-data-snapshotsdataset. - AdamW + cosine schedule, max-seq-len 8192, bf16, single H100 80 GB.
- See
code2lora/code2lorafor the trainer code.
Companion model
code2lora/code2lora-gru -- the streaming-recurrent variant trained on
commit deltas.
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