Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use ducatte/sequence_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ducatte/sequence_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ducatte/sequence_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ducatte/sequence_classification") model = AutoModelForSequenceClassification.from_pretrained("ducatte/sequence_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d313c3bb3d9f6b862a9062ceb993a5318a980575712ef88e3ac9e414e938d5c
- Size of remote file:
- 268 MB
- SHA256:
- 20120363bdd56e1ab9a640654acd0dc77317eefa335bf1e2f1d28a324d77069b
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