triton
Datasets
All datasets matching “triton”ComfyUI_portable_torch_2.13.0_cu130_cp313_sageattention_tritonI recommend run run_nvidia_gpu.bat for more stability work with this comfyui build
I put Extra_Model_Paths_Maker.bat if you need synchronize models path from current ComfyUI Build. Put this .bat file into your model path, double click on Extra_Model_Paths_Maker.bat and extra_model_paths.yaml will appear in model path. Then copy/cut extra_model_paths.yaml and put into new ComfyUI Build into ComfyUI_windows_portable\ComfyUI . Now the models are visible in the new ComfyUI build
The build includes… See the full description on the dataset page: https://huggingface.co/datasets/StefanFalkok/ComfyUI_portable_torch_2.13.0_cu130_cp313_sageattention_triton.so100_pick_place_tapeeval_so100_test_ppt2_pi0_2This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.0",
"robot_type": "so100",
"total_episodes": 10,
"total_frames": 8881,
"total_tasks": 1,
"total_videos": 30,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 30,
"splits": {
"train": "0:10"
},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/triton7777/eval_so100_test_ppt2_pi0_2.triton-gpu-latency
Triton GPU Latency Dataset
A large dataset of PyTorch problems (mostly from KernelBench) paired with candidate Triton-kernel implementations and their measured GPU runtimes generated by MakoraGenerate. Each row is a self-contained Python program that defines (1) a reference Model written with plain PyTorch ops and (2) a ModelNew that re-implements the same forward pass with a hand-written or generated Triton kernel. The label is the runtime of executing ModelNew.
Built for… See the full description on the dataset page: https://huggingface.co/datasets/makora-ai/triton-gpu-latency.TritonCast_inference_datasetsadvanced-triton-kernel-traces