After hours of struggling with the installation I am getting this error. Any solution plz
(audiogpt) C:\sd\AudioGPT>python audio-chatgpt.py
Initializing AudioGPT
Initializing T2I to cuda:0
C:\Users\nitin\miniconda3\envs\audiogpt\lib\site-packages\huggingface_hub\file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
warnings.warn(
unet\diffusion_pytorch_model.safetensors not found
Initializing ImageCaptioning to cuda:0
Initializing Make-An-Audio to cuda:0
LatentDiffusion_audio: Running in eps-prediction mode
DiffusionWrapper has 160.22 M params.
making attention of type 'vanilla' with 256 in_channels
making attention of type 'vanilla' with 256 in_channels
making attention of type 'vanilla' with 512 in_channels
making attention of type 'vanilla' with 512 in_channels
making attention of type 'vanilla' with 512 in_channels
Working with z of shape (1, 4, 106, 106) = 44944 dimensions.
making attention of type 'vanilla' with 512 in_channels
making attention of type 'vanilla' with 512 in_channels
making attention of type 'vanilla' with 512 in_channels
making attention of type 'vanilla' with 512 in_channels
making attention of type 'vanilla' with 256 in_channels
making attention of type 'vanilla' with 256 in_channels
making attention of type 'vanilla' with 256 in_channels
C:\Users\nitin\miniconda3\envs\audiogpt\lib\site-packages\huggingface_hub\file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
warnings.warn(
tokenizer_config.json: 100%|████████████████████████████████████████████████████████████████| 48.0/48.0 [00:00<?, ?B/s]
config.json: 100%|████████████████████████████████████████████████████████████████████| 570/570 [00:00<00:00, 36.6kB/s]
vocab.txt: 100%|█████████████████████████████████████████████████████████████████████| 232k/232k [00:00<00:00, 531kB/s]
tokenizer.json: 100%|████████████████████████████████████████████████████████████████| 466k/466k [00:00<00:00, 735kB/s]
model.safetensors: 100%|████████████████████████████████████████████████████████████| 440M/440M [00:35<00:00, 12.3MB/s]
Some weights of the model checkpoint at bert-base-uncased were not used when initializing BertModel: ['cls.predictions.transform.LayerNorm.weight', 'cls.predictions.transform.dense.bias', 'cls.predictions.transform.dense.weight', 'cls.seq_relationship.weight', 'cls.predictions.bias', 'cls.predictions.transform.LayerNorm.bias', 'cls.seq_relationship.bias']
- This IS expected if you are initializing BertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing BertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
TextEncoder comes with 111.32 M params.
Traceback (most recent call last):
File "audio-chatgpt.py", line 1377, in <module>
bot = ConversationBot()
File "audio-chatgpt.py", line 1057, in __init__
self.t2a = T2A(device="cuda:0")
File "audio-chatgpt.py", line 144, in __init__
self.sampler = self._initialize_model('text_to_audio/Make_An_Audio/configs/text_to_audio/txt2audio_args.yaml', 'text_to_audio/Make_An_Audio/useful_ckpts/ta40multi_epoch=000085.ckpt', device=device)
File "audio-chatgpt.py", line 150, in _initialize_model
model.load_state_dict(torch.load(ckpt, map_location='cpu')["state_dict"], strict=False)
File "C:\Users\nitin\miniconda3\envs\audiogpt\lib\site-packages\torch\serialization.py", line 713, in load
return _legacy_load(opened_file, map_location, pickle_module, **pickle_load_args)
File "C:\Users\nitin\miniconda3\envs\audiogpt\lib\site-packages\torch\serialization.py", line 920, in _legacy_load
magic_number = pickle_module.load(f, **pickle_load_args)
_pickle.UnpicklingError: pickle data was truncated
After hours of struggling with the installation I am getting this error. Any solution plz