This is very much a beginner question. I am trying to load a  fine tuned model for multi-label text classification. Fine-tuned on 11 labels, bert-base-uncased.
I just want to feed new text to the model and get the labels predicted to be associated with the text.
I have looked everywhere and cannot find an example of how to actually load and use a fine-tuned model on new data after fine tuning is complete.
I have the model saved via:
model.save_pretrained("fine_tuned_model")
I can load the model back with:
model = AutoModelForSequenceClassification.from_pretrained("fine_tuned_model", from_tf=False, config=config)
From here I am stuck. I have been told to use model.predict("text") but when I do I get the following error:
'BertForSequenceClassification' object has no attribute 'predict'
I hope this makes sense and any help would be greatly appreciated.