I'm also on a 50-series GPU. You can upgrade both pytorch and xformers as they've just released stable builds for cuda 12.8, but RVC seems to rely on torch-directml, which hasn't been updated to support pytorch 2.7, and there may be something else that I'm missing, too.

I upgraded xformers and torch by doing this inside the RVC directory:

runtime\python.exe -m pip uninstall torch torchvision torchaudio xformers
runtime\python.exe -m pip install torch torchvision torchaudio xformers --index-url https://download.pytorch.org/whl/cu128

In the meantime, you can run on CPU if you're not using the real-time GUI by opening configs\config.py and change if torch.cuda.is_available(): to if False:. I was still getting errors with my updated packages, though, so I had to switch them back to torch 2.0.0+cu118 , torch-directml 0.2.0.dev230426 and xformers 0.0.19.

If someone else out there knows how to get it running, please share.

I'm also on a 50-series GPU. You can upgrade both pytorch and xformers as they've just released stable builds for cuda 12.8, but RVC seems to rely on torch-directml, which hasn't been updated to support pytorch 2.7, and there may be something else that I'm missing, too.

I upgraded xformers and torch by doing this inside the RVC directory:

runtime\python.exe -m pip uninstall torch torchvision torchaudio xformers
runtime\python.exe -m pip install torch torchvision torchaudio xformers --index-url https://download.pytorch.org/whl/cu128

In the meantime, you can run on CPU if you're not using the real-time GUI by opening configs\config.py and change if torch.cuda.is_available(): to if False:. I was still getting errors with my updated packages, though, so I had to switch them back to torch 2.0.0+cu118 , torch-directml 0.2.0.dev230426 and xformers 0.0.19.

If someone else out there knows how to get it running, please share.

me too I am facing the same.. I was able to train a new model but on CPU. Also I am facing another issue while converting I get an error timed out. which is very annoying

You may try to run go-realtime-gui.bat and if you got something like:

AttributeError: 'RVC' object has no attribute 'tgt_sr'

you can patch runtime/Lib/site-packages/fairseq/checkpoint_utils.py

search for any torch.load and add weights_only=False to bypass security policy in new version of PyTorch

BTW I am using RTX 4080 so I am not sure with RTX 50 series

I just updated my PyTorch to 2.7.0 for better speed, then the problem occured, and after patching it got worked

Hope it will help

@haofanurusai

Thanks, I found this and it fixes things partially. However, training wasn't working, I had to do some fixes, after these training starts and finishes, although UI shows 'Error' in bottom right corner.

I got these features working (not that thoroughly tested, just 5 minutes testing on each):

• Inference
• Training
• Merging models (everything else too on this page seems to be working)
• Onnx export not working (edit - works, but not with simplify)

I don't know about this onnx export, never used it, don't know how it should work. It does something for a while, progress bar fills, then I get "Something went wrong: connection errored out". I found two threads about this here in this repo, but no solution, unless I missed it. Edit - I found the culprit for this export onnx error, it is this line in the export.py:

model, _ = onnxsim.simplify(ExportedPath)

I bypassed it, but then you have to write some code around it, and I also had to change infer-web.py file's def export_onnx(ModelPath, ExportedPath) function, so that it returns something else than None, otherwise Gradio UI seems to get stuck.

Not sure what the proper fix would be, but at least the model exports now without errors, although the simplify operation is skipped.