Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use schoenml/bert-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use schoenml/bert-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="schoenml/bert-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("schoenml/bert-emotion") model = AutoModelForSequenceClassification.from_pretrained("schoenml/bert-emotion") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b581ae4b9a165f55a15ab779ce5aea254220496b233f3887168951ecb2eb0137
- Size of remote file:
- 263 MB
- SHA256:
- c622c81eb14465ba121d72300e28840dab4c17726eeb2478e9ff4bdebae973b2
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