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Happy Transformer is an package built on top of Hugging Face's transformer library that makes it easy to utilize state-of-the-art NLP models.
| Public Methods | Basic Usage | Training |
|---|---|---|
| Text Generation | ✔ | ✔ |
| Text Classification | ✔ | ✔ |
| Word Prediction | ✔ | ✔ |
| Question Answering | ✔ | ✔ |
| Text-to-Text | ✔ | ✔ |
| Next Sentence Prediction | ✔ | |
| Token Classification | ✔ |
pip install happytransformerfrom happytransformer import HappyWordPrediction
#--------------------------------------#
happy_wp = HappyWordPrediction() # default uses distilbert-base-uncased
result = happy_wp.predict_mask("I think therefore I [MASK]")
print(result) # [WordPredictionResult(token='am', score=0.10172799974679947)]
print(result[0].token) # am- Eric Fillion Lead Maintainer
- Ted Brownlow Maintainer
Text generation with training (GPT-Neo)
Text classification (training)
Text classification (hate speech detection)
Text classification (sentiment analysis)
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