TEXTA Bert Tagger
Installation
Using built package
pip install texta-bert-tagger
Using Git
pip install git+https://git.texta.ee/texta/texta-bert-tagger-python.git
Testing
python -m pytest -v tests
Documentation
Documentation for version 1.* is available here.
Documentation for version 2.* is available here.
Documentation for version 3.* is available here.
Usage (for versions >=3..)
Fine-tune BERT model
from texta_bert_tagger.tagger import BertTagger
bert_tagger = BertTagger()
data_sample = {"good": ["It was a nice day.", "All was well."], "bad": ["It was horrible.", "What a disaster."]}
# Train a model
# pos_label - used in metrics (precision, recall, f1-score etc) calculations as true label
bert_tagger.train(data_sample, pos_label="bad", n_epochs=2)
# Predict
result = bert_tagger.tag_text("How awful!")
print(result)
Output
[{"prediction": "bad", "probability": 0.55200404, "attributions": {}}]
1 maintainer
Release files for texta-bert-tagger 3.0.2
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Source distribution (sdist)
| File | Size | Uploaded | |
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| texta-bert-tagger-3.0.2.tar.gz | 30.5 kB | Details |
Release files / texta-bert-tagger-3.0.2.tar.gz
| Download URL | texta-bert-tagger-3.0.2.tar.gz |
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