Text Classification
Transformers
PyTorch
Safetensors
English
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use librarian-bots/model-card-dataset-mentions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use librarian-bots/model-card-dataset-mentions with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="librarian-bots/model-card-dataset-mentions")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("librarian-bots/model-card-dataset-mentions") model = AutoModelForSequenceClassification.from_pretrained("librarian-bots/model-card-dataset-mentions") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e6efad6d898c3c0d876f06dd3c54824033b49dbc2cd3eb56ca9a5f5710e0266
- Size of remote file:
- 433 MB
- SHA256:
- 563c9f09a85f9587978fd0edb02a5329bbd04f1d6f12971b5395fdc4c7eedea2
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