Instructions to use ceselder/lol-loracle-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ceselder/lol-loracle-v1 with PEFT:
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- Notebooks
- Google Colab
- Kaggle
LoL LoRAcle v1
Loracle (weight-reading interpreter) fine-tuned from ceselder/loracle-pretrain-v7-sweep-A-oneq-final-step3120 on Q/A about the 1,170 Lots-of-LoRAs Super-NaturalInstructions tasks ported to Qwen3-14B (see ceselder/lots-of-loras-qwen3-14b).
Training
- 4520 Q/A pairs over 1,130 train LoRAs (40 held-out)
- 565 steps, 1 epoch, lr=1e-5 linear, grad_accum=8
- val_loss: 4.0932 (step 0, v7 baseline) -> 1.3244 (step 565, final)
- wandb: https://wandb.ai/adamkarvonen/lora-oracles/runs/m3ar3wzq
Files
interpreter/-- peft LoRA adapter (rank 256)encoder.pt,ao.pt-- AOEncoder + norm-match hook paramsloracle_config.yaml-- training config
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