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Companion artifact for GPU Forecasters: Language Models as Selective Surrogates for Kernel Runtime Optimization. Code: codezakh/gpu-surrogates.

LoRA adapter for openai/gpt-oss-20b fine-tuned with the correctness reward to forecast kernel speedups.

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from peft import AutoPeftModelForCausalLM
model = AutoPeftModelForCausalLM.from_pretrained("codezakh/gpu-forecasters-gpt-oss-20b-correctness")

Training data

codezakh/gpu-forecasters-rl-training-pool.

Reproducing

See runbook/02_train_surrogate.py in the paper repo (codezakh/gpu-surrogates).

Citation

@article{khan2026gpuforecasters,
  title={GPU Forecasters: Language Models as Selective Surrogates for Kernel Runtime Optimization},
  author={Khan, Zaid and Chen, Justin Chih-Yao and Cho, Jaemin and Stengel-Eskin, Elias and Bansal, Mohit},
  journal={arXiv preprint arXiv:2605.31464},
  year={2026}
}
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Paper for codezakh/gpu-forecasters-gpt-oss-20b-correctness