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:
- a6b176240a519cc4b9cf1f7a51036865bcff57e1668ac5ae6e79132fa2fbbd24
- Size of remote file:
- 3.96 kB
- SHA256:
- 747b48648e31d7c77e6d6ae4d18945aeb348a8dbb7c5c0b520f101eb2ae96ced
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