Token Classification
PyTorch
GLiNER
English
gliformer
deberta
named-entity-recognition
text-classification
relation-extraction
structured-extraction
feature-extraction
document-understanding
Instructions to use knowledgator/gliformer-base-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use knowledgator/gliformer-base-v1 with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("knowledgator/gliformer-base-v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b9776fc942de92e920b60bdc5e411e3563ff8d783fe27e1efe37dfa9da7701f8
- Size of remote file:
- 1.06 GB
- SHA256:
- b3b44b6e4f665e8631057056cf3c235cbfedd979d37f90e57b176e18e30ccd4b
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