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", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("autoevaluate/entity-extraction") model = AutoModelForTokenClassification.from_pretrained("autoevaluate/entity-extraction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 891708570f6bc769ed5889a7a960f20e7e1d15fd2f2594f2d045c6d827ccb519
- Size of remote file:
- 265 MB
- SHA256:
- cdd9062abcff80fabefa6d4f83dd773fd5573347811697f763da3d559fc18bdc
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