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:
- 81244cec9172ba7d306ee3eaaca2841d96007a7e6bf127651584f75a54401b58
- Size of remote file:
- 3.18 kB
- SHA256:
- c91245525b6a35d02438778b3a710b2cdbe70f5c66e21a2bab6d190c0660f580
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