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README.md
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## How to use
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```python
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>>> from .model import BertForTokenAndSequenceJointClassification
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>>> model = BertForTokenAndSequenceJointClassification.from_pretrained(
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>>> "QCRI/PropagandaTechniquesAnalysis-en-BERT",
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>>> revision="v0.1.0",
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>>> )
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```
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## How to use
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```python
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>>> from transformers import BertTokenizerFast
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>>> from .model import BertForTokenAndSequenceJointClassification
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>>>
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>>> tokenizer = BertTokenizerFast.from_pretrained('bert-base-cased')
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>>> model = BertForTokenAndSequenceJointClassification.from_pretrained(
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>>> "QCRI/PropagandaTechniquesAnalysis-en-BERT",
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>>> revision="v0.1.0",
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>>> )
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>>>
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>>> inputs = tokenizer.encode_plus("Hello, my dog is cute", return_tensors="pt")
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>>> outputs = model(**inputs)
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>>> sequence_class_index = torch.argmax(outputs.sequence_logits, dim=-1)
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>>> sequence_class = model.sequence_tags[sequence_class_index[0]]
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>>> token_class_index = torch.argmax(outputs.token_logits, dim=-1)
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>>> tokens = tokenizer.convert_ids_to_tokens(inputs.input_ids[0][1:-1])
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>>> tags = [model.token_tags[i] for i in token_class_index[0].tolist()[1:-1]]
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```
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