Token Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
Instructions to use autoevaluate/entity-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autoevaluate/entity-extraction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="autoevaluate/entity-extraction")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("autoevaluate/entity-extraction") model = AutoModelForTokenClassification.from_pretrained("autoevaluate/entity-extraction") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 609f4198b0b0fca190ae59b2aab704be0a1262e80ef7bfa7d458c46c3deaed29
- Size of remote file:
- 3.25 kB
- SHA256:
- 2d1c6ac821fc97102a539ed0dc7e508dd3cb472466b36d81affda3e3476950e3
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