#Error: Error: RVC model not properly initialized. on Vonovox

1 messages · Page 1 of 1 (latest)

proven jacinth
#

Full GPU Name:
Zotac Gaming GeForce RTX 5070 Solid OC – 12GB GDDR7 (Desktop)

CPU:
AMD Ryzen 5 7500F (6 cores / 12 threads)

Motherboard:
Gigabyte A620M H (AM5)

RAM:
16GB DDR5 5600 MHz (2×8GB, Dual Channel)

Storage:
1TB WD Blue SN580 NVMe (PCIe 4.0)

Power Supply:
SQ-WHITE Silent 700W – 80 PLUS

Case:
SQ-Tower 01M RGB (mesh front, tempered glass)

Cooling:

CPU Cooler: SQ-COOLER 02U (120W TDP)

Case Fans: 3×120mm front intake + 1×120mm rear exhaust

Operating System:
Windows 11

Detailed Description of the Problem

Hello, when i click start on Vonovox after loading a model this error appears:

Starting voice conversion...
Starting warmup sequence
Traceback (most recent call last):
File "core/inference/cuvc.py", line 216, in core.inference.cuvc.RVC.init
RuntimeError: CUDA error: no kernel image is available for execution on the device
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.

Error: RVC model not properly initialized. Check above error for more details.
Failed to initialize audio processing
Critical error in start_vc: Failed to initialize audio processing
Traceback (most recent call last):
File "gui/gui.py", line 1495, in gui.gui.GUI.start_vc
File "gui/gui.py", line 1532, in gui.gui.GUI.initialize_voice_conversion
RuntimeError: Failed to initialize audio processing

Does anybody knows how to fix it? Thanks

#

also got this message at the start :

NVIDIA GeForce RTX 5070 with CUDA capability sm_120 is not compatible with the current PyTorch installation.
The current PyTorch install supports CUDA capabilities sm_50 sm_60 sm_61 sm_70 sm_75 sm_80 sm_86 sm_90.
If you want to use the NVIDIA GeForce RTX 5070 GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/

PyTorch

Set up PyTorch easily with local installation or supported cloud platforms.

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