Instructions to use pysentimiento/bert-pt-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pysentimiento/bert-pt-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pysentimiento/bert-pt-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pysentimiento/bert-pt-emotion") model = AutoModelForSequenceClassification.from_pretrained("pysentimiento/bert-pt-emotion", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65346c57cdd1c772c789d2012955990d4d7e11f666e0660cffc4ce937470023d
- Size of remote file:
- 436 MB
- SHA256:
- 7efb15f9e82b7c63976aa10ced240ea411aeaaa84a8f6909e30d1ee947ce43d4
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