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Some weights of the model checkpoint at Rostlab/prot_bert were not used when initializing BertModel: ['cls.seq_relationship.bias', 'cls.predictions.bias', 'cls.predictions.transform.LayerNorm.bias', 'cls.predictions.decoder.bias', 'cls.seq_relationship.weight', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.transform.dense.bias', 'cls.predictions.transform.dense.weight', 'cls.predictions.decoder.weight']
- 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).
Model: ProtBERT
Using GPU
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Some weights of the model checkpoint at Rostlab/prot_bert_bfd were not used when initializing BertModel: ['cls.seq_relationship.bias', 'cls.predictions.bias', 'cls.predictions.transform.LayerNorm.bias', 'cls.predictions.decoder.bias', 'cls.seq_relationship.weight', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.transform.dense.bias', 'cls.predictions.transform.dense.weight', 'cls.predictions.decoder.weight']
- 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).
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Model: ProtBERT-BFD
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Traceback (most recent call last):
File "save_representations_frozen_full.py", line 28, in <module>
tokenizer = T5Tokenizer.from_pretrained(settings.PROTT5["model"])
File "/home/h_ghazik/python_venv/lib/python3.7/site-packages/transformers/utils/import_utils.py", line 1050, in __getattribute__
requires_backends(cls, cls._backends)
File "/home/h_ghazik/python_venv/lib/python3.7/site-packages/transformers/utils/import_utils.py", line 1038, in requires_backends
raise ImportError("".join(failed))
ImportError:
T5Tokenizer requires the SentencePiece library but it was not found in your environment. Checkout the instructions on the
installation page of its repo: https://github.com/google/sentencepiece#installation and follow the ones
that match your environment. Please note that you may need to restart your runtime after installation.