kernelbook
KernelBook
Overview
dataset_permissive{.json/.parquet} is a curated collection of pairs of pytorch programs and equivalent triton code (generated by torch inductor) which can be used to train models to translate pytorch code to triton code.
The triton code was generated using PyTorch 2.5.0 so for best results during evaluation / running the triton code we recommend using that version of pytorch.
Dataset Creation
The dataset was created through the following process:… See the full description on the dataset page: https://huggingface.co/datasets/GPUMODE/KernelBook.kernelbook-glm4-evalskernelbook-opus4.8-multiturn-traces
KernelBook → Triton: Multi-Turn Generation Traces (Opus 4.8)
Multi-turn agentic traces of Claude Opus 4.8 converting PyTorch modules into
Triton GPU kernels. Each row is one problem from
GPUMODE/KernelBook: the model
writes a kernel, runs it on a GPU against the reference, reads the
correctness + speedup feedback, and iterates — so every trace is a grounded,
tool-using optimization loop, not a single-shot completion.
How it was generated
Model: claude-opus-4-8… See the full description on the dataset page: https://huggingface.co/datasets/ppbhatt500/kernelbook-opus4.8-multiturn-traces.kernelbook-kimi_k2_thinking-evalskernelbook-kimi_k2_thinking-evals-synthetic-promptsKernelBook-messages