gritty crypt
I've tried changing from Python 3.11 to 3.10, I've messed with the Torch Version, I messed with ffmpeg. I don't know what else to do.
<RVC module> Received request for list of RVC models
<RVC module> Searching model in data/models/rvc/
> Found model folder Nicole
> index: added_IVF1003_Flat_nprobe_1_NicoleClassOf09_v2.index
> pth: NicoleClassOf09_e900_s20700.pth
> Valid folder added to list
2025-05-22 16:02:54 | INFO | werkzeug | 127.0.0.1 - - [22/May/2025 16:02:54] "POST /api/voice-conversion/rvc/get-models-list HTTP/1.1" 200 -
<RVC module> received: <FileStorage: 'record' ('audio/wav')>
<RVC module> Received audio conversion request with model {'modelName': 'Nicole', 'pitchExtraction': 'dio', 'pitchOffset': '0', 'indexRate': '0.85', 'filterRadius': '3', 'rmsMixRate': '1', 'protect': '0.33'}
<RVC module> Check for pth file in data/models/rvc/Nicole/
> set pth as NicoleClassOf09_e900_s20700.pth
<RVC module> Check for index file data/models/rvc/Nicole/
> set index as added_IVF1003_Flat_nprobe_1_NicoleClassOf09_v2.index
<RVC module> loading data/models/rvc/Nicole/NicoleClassOf09_e900_s20700.pth
loading data/models/rvc/Nicole/NicoleClassOf09_e900_s20700.pth
C:\Users\emv20\anaconda3\envs\extras\lib\site-packages\torch\nn\utils\weight_norm.py:143: FutureWarning: `torch.nn.utils.weight_norm` is deprecated in favor of `torch.nn.utils.parametrizations.weight_norm`.
WeightNorm.apply(module, name, dim)
gin_channels: 256 self.spk_embed_dim: 109
<All keys matched successfully>
Traceback (most recent call last):
File "C:\Users\emv20\SillyTavern-extras\modules\voice_conversion\rvc\rvc.py", line 216, in vc_single
load_hubert()
File "C:\Users\emv20\SillyTavern-extras\modules\voice_conversion\rvc\rvc.py", line 128, in load_hubert
models, _, _ = checkpoint_utils.load_model_ensemble_and_task(
File "C:\Users\emv20\SillyTavern-extras\modules/voice_conversion\fairseq\checkpoint_utils.py", line 425, in load_model_ensemble_and_task
state = load_checkpoint_to_cpu(filename, arg_overrides)
File "C:\Users\emv20\SillyTavern-extras\modules/voice_conversion\fairseq\checkpoint_utils.py", line 315, in load_checkpoint_to_cpu
state = torch.load(f, map_location=torch.device("cpu"))
File "C:\Users\emv20\anaconda3\envs\extras\lib\site-packages\torch\serialization.py", line 1524, in load
raise pickle.UnpicklingError(_get_wo_message(str(e))) from None
_pickle.UnpicklingError: Weights only load failed. This file can still be loaded, to do so you have two options, do those steps only if you trust the source of the checkpoint.
(1) In PyTorch 2.6, we changed the default value of the `weights_only` argument in `torch.load` from `False` to `True`. Re-running `torch.load` with `weights_only` set to `False` will likely succeed, but it can result in arbitrary code execution. Do it only if you got the file from a trusted source.
(2) Alternatively, to load with `weights_only=True` please check the recommended steps in the following error message.
WeightsUnpickler error: Unsupported global: GLOBAL fairseq.data.dictionary.Dictionary was not an allowed global by default. Please use `torch.serialization.add_safe_globals([fairseq.data.dictionary.Dictionary])` or the `torch.serialization.safe_globals([fairseq.data.dictionary.Dictionary])` context manager to allowlist this global if you trust this class/function.
Check the documentation of torch.load to learn more about types accepted by default with weights_only https://pytorch.org/docs/stable/generated/torch.load.html.
'NoneType' object has no attribute 'dtype'
2025-05-22 16:03:10 | INFO | werkzeug | 127.0.0.1 - - [22/May/2025 16:03:10] "POST /api/voice-conversion/rvc/process-audio HTTP/1.1" 500 -
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