Pytorch support for sm120

deployment
86

For anyone running CSM-1B (Sesame’s TTS model) on RTX 5090 — I got it working at 0.46x RTF with CUDA graph replay using nightly cu128. Had to patch HF Transformers in 4 places: StaticCache index_copy_ → slice assignment, 3x arange fixes in modeling_csm.py, and cudagraph_mark_step_begin calls in the generate loop. Full pipeline + auto-patcher here: https://github.com/D3velop-llc/csm-rtx5090

87

this worked on my rtx 5050 too. Thank you very much.

88

:white_check_mark: RTX 5050 + CUDA 12.8 + PyTorch (Working Setup)

Hi everyone,

I recently set up PyTorch on a machine with an NVIDIA RTX 5050 Laptop GPU, and wanted to share a working configuration since older/stable builds didn’t properly support this GPU architecture.

:wrench: Working Setup

  • GPU: NVIDIA GeForce RTX 5050 Laptop GPU

  • CUDA Toolkit: 12.8

  • Python: 3.11

  • PyTorch: Nightly build (CUDA 12.8)

:package: Installation Command

pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128

:white_check_mark: Verification

import torch

print("Torch version:", torch.__version__)
print("CUDA available:", torch.cuda.is_available())

if torch.cuda.is_available():
    print("GPU:", torch.cuda.get_device_name(0))

:light_bulb: Notes

  • Nightly builds with cu128 worked correctly and enabled full GPU acceleration.

Hope this helps anyone trying to get newer RTX GPUs working with PyTorch :+1:

89

That’s wrong as all of our binaries using CUDA >= 12.8 support the Blackwell architecture.

90

yes, i updated the mistake.

91

Hi Sean_V, you need for this the version of pytorch 2.11.0+cu128, This is because previous version didn’t have this version