runtime error

Exit code: 1. Reason: nv_embed.conv.weight_v', 'wav2vec2.encoder.pos_conv_embed.conv.weight_g'] - This IS expected if you are initializing Wav2Vec2ForCTC 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 Wav2Vec2ForCTC from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model). Some weights of Wav2Vec2ForCTC were not initialized from the model checkpoint at ai4bharat/indicwav2vec_v1_gujarati and are newly initialized: ['wav2vec2.encoder.pos_conv_embed.conv.parametrizations.weight.original0', 'wav2vec2.encoder.pos_conv_embed.conv.parametrizations.weight.original1'] You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference. Traceback (most recent call last): File "/home/user/app/app.py", line 10, in <module> transcriber_gujarati = pipeline("automatic-speech-recognition", model="ai4bharat/indicwav2vec_v1_gujarati") File "/home/user/.local/lib/python3.10/site-packages/transformers/pipelines/__init__.py", line 967, in pipeline tokenizer = AutoTokenizer.from_pretrained( File "/home/user/.local/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py", line 808, in from_pretrained return tokenizer_class_py.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs) File "/home/user/.local/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 2012, in from_pretrained raise EnvironmentError( OSError: Can't load tokenizer for 'ai4bharat/indicwav2vec_v1_gujarati'. If you were trying to load it from 'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure 'ai4bharat/indicwav2vec_v1_gujarati' is the correct path to a directory containing all relevant files for a Wav2Vec2CTCTokenizer tokenizer.

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