runtime error

B/s] Downloading pytorch_model.bin: 88%|████████▊ | 545M/619M [00:05<00:00, 103MB/s] Downloading pytorch_model.bin: 90%|████████▉ | 556M/619M [00:05<00:00, 95.8MB/s] Downloading pytorch_model.bin: 93%|█████████▎| 577M/619M [00:05<00:00, 87.8MB/s] Downloading pytorch_model.bin: 97%|█████████▋| 598M/619M [00:05<00:00, 107MB/s] Downloading pytorch_model.bin: 100%|█████████▉| 619M/619M [00:06<00:00, 99.2MB/s] Downloading pytorch_model.bin: 100%|██████████| 619M/619M [00:06<00:00, 102MB/s] Traceback (most recent call last): File "/home/user/app/app.py", line 8, in <module> p = pipeline("automatic-speech-recognition", model="jjyaoao/speechT5_asr_dev-clean") File "/home/user/.local/lib/python3.10/site-packages/transformers/pipelines/__init__.py", line 788, in pipeline framework, model = infer_framework_load_model( File "/home/user/.local/lib/python3.10/site-packages/transformers/pipelines/base.py", line 269, in infer_framework_load_model model = model_class.from_pretrained(model, **kwargs) File "/home/user/.local/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py", line 493, in from_pretrained return model_class.from_pretrained( File "/home/user/.local/lib/python3.10/site-packages/transformers/modeling_utils.py", line 2903, in from_pretrained ) = cls._load_pretrained_model( File "/home/user/.local/lib/python3.10/site-packages/transformers/modeling_utils.py", line 3310, in _load_pretrained_model raise RuntimeError(f"Error(s) in loading state_dict for {model.__class__.__name__}:\n\t{error_msg}") RuntimeError: Error(s) in loading state_dict for SpeechT5ForSpeechToText: size mismatch for speecht5.decoder.prenet.embed_positions.weights: copying a param with shape torch.Size([522, 768]) from checkpoint, the shape in current model is torch.Size([454, 768]). You may consider adding `ignore_mismatched_sizes=True` in the model `from_pretrained` method.

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