All the dependencies have been downloaded, and hubert_base.pt has been placed in the "Multi-Model-RVC-Inference" folder. Upon running app.py, this error appeared:

Traceback (most recent call last):
File "/Users/axelerikswenson/Desktop/Multi-Model-RVC-Inference/app.py", line 344, in
categories = load_model()
File "/Users/axelerikswenson/Desktop/Multi-Model-RVC-Inference/app.py", line 125, in load_model
with open(f"weights/{category_folder}/model_info.json", "r", encoding="utf-8") as f:
FileNotFoundError: [Errno 2] No such file or directory: 'weights/CATEGORY_FOLDER_PATH/model_info.json'
(base) axelerikswenson@Axels-MBP Multi-Model-RVC-Inference %

Considering all the files have been downloaded / and not tampered with, I honestly have no clue what could be the issue. Anyone have any ideas?

Hi, thanks for open sourcing the inference code. I wonder if there is a CLI or API version of the inference code, not the Gradio version. Thanks!

di lognya terlihat "converting" tapi dalam banayk model secara bersamaan, normal gk nih mas?

Hello I loaded up my model and I try to convert and I get this error.

Traceback (most recent call last):
File "/home/reaktor/Downloads/Multi-Model-RVC-Inference/app.py", line 101, in vc_fn
audio_opt = vc.pipeline(
File "/home/reaktor/Downloads/Multi-Model-RVC-Inference/vc_infer_pipeline.py", line 396, in pipeline
self.vc(
File "/home/reaktor/Downloads/Multi-Model-RVC-Inference/vc_infer_pipeline.py", line 216, in vc
npy = np.sum(big_npy[ix] * np.expand_dims(weight, axis=2), axis=1)
IndexError: index -1 is out of bounds for axis 0 with size 0

Full log

2023-11-26 21:07:04 | INFO | faiss.loader | Loading faiss with AVX2 support.
2023-11-26 21:07:04 | INFO | faiss.loader | Could not load library with AVX2 support due to:
ModuleNotFoundError("No module named 'faiss.swigfaiss_avx2'")
2023-11-26 21:07:04 | INFO | faiss.loader | Loading faiss.
2023-11-26 21:07:05 | INFO | faiss.loader | Successfully loaded faiss.
INFO: No supported Nvidia GPU found, use CPU instead
2023-11-26 21:07:05 | INFO | fairseq.tasks.hubert_pretraining | current directory is I:\AI\voice\test-model\Multi-Model-RVC-Inference
2023-11-26 21:07:05 | INFO | fairseq.tasks.hubert_pretraining | HubertPretrainingTask Config {'_name': 'hubert_pretraining', 'data'ype': transformer, 'dropout': 0.1, 'attention_dropout': 0.1, 'activation_dropout': 0.0, 'encoder_layerdrop': 0.05, 'dropout_input': 0.1, 'dropout_features': 0.1, 'final_dim': 256, 'untie_final_proj': True, 'layer_norm_first': False, 'conv_feature_layers': '[(512,10,5)] + [(512,3,2)] * 4 + [(512,2,2)] * 2', 'conv_bias': False, 'logit_temp': 0.1, 'target_glu': False, 'feature_grad_mult': 0.1, 'mask_lengype': transformer, 'dropout': 0.1, 'attention_dropout': 0.1, 'activation_dropout': 0.0, 'encoder_layerdrop': 0.05, 'dropout_input': 0.1, 'dropout_features': 0.1, 'final_dim': 256, 'untie_final_proj': True, 'layer_norm_first': False, 'conv_feature_layers': '[(512,10,5)] + [(512,3,2)] * 4 + [(512,2,2)] * 2', 'conv_bias': False, 'logit_temp': 0.1, 'target_glu': False, 'feature_grad_mult': 0.1, 'mask_length': 10, 'mask_prob': 0.8, 'mask_selection': static, 'mask_other': 0.0, 'no_mask_overlap': False, 'mask_min_space': 1, 'mask_channel_length': 10, 'mask_channel_prob': 0.0, 'mask_channel_selection': static, 'mask_channel_other': 0.0, 'no_mask_channel_overlap': False, 'mask_channel_min_space': 1, 'conv_pos': 128, 'conv_pos_groups': 16, 'latent_temp': [2.0, 0.5, 0.999995], 'skip_masked': False, 'skip_nomask': False, 'checkpoint_activations': False, 'required_seq_len_multiple': 2, 'depthwise_conv_kernel_size': 31, 'attn_type': '', 'pos_enc_type': 'abs', 'fp16': False}
C:\Users: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.
warnings.warn("torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.")
gin_channels: 256 self.spk_embed_dim: 109
All keys matched successfully
Model loaded: lisa-jp / model.index | (V2)
Traceback (most recent call last):
File "app.py", line 419, in
categories = load_model()
File "app.py", line 182, in load_model
category_count += 1
UnboundLocalError: local variable 'category_count' referenced before assignment

model_info.json

{
    "lisa-jp": {
        "enable": true,
        "model_path": "model.pth",
        "title": "lisa-jp",
        "cover": "CHARACTER_IMAGE",
        "feature_retrieval_library": "model.index",
        "author": "iroaK"
    }
}

folder_info.json

{
    "Mondstadt":{
        "enable": true,
        "title": "mondstadt",
        "folder_path": "mondstadt",
        "description": "RVC genshin impact"
    },
    "Liyue":{
        "enable": true,
        "title": "liyue",
        "folder_path": "liyue",
        "description": "RVC genshin impact"
    }
}

Folder Structure

weights/
├── liyue
├── mondstadt/
│   ├── lisa-jp
│   └── model_info.json
└── folder_info.json

Ada saran gan?