Token Classification
GLiNER
PyTorch
ONNX
English
multilingual
named-entity-recognition
information-extraction
legal
contracts
nlp
Instructions to use agilelab-org/Contractner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use agilelab-org/Contractner with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("agilelab-org/Contractner") text = "Cristiano Ronaldo dos Santos Aveiro was born on 5 February 1985 in Funchal, Madeira, Portugal." labels = ["person", "date", "location"] entities = model.predict_entities(text, labels) for entity in entities: print(entity["text"], "=>", entity["label"]) - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from agilelab-org/Contractner: direct link, hf CLI and curl.
- Browser
- Download file 286 Bytes
-
https://huggingface.co/agilelab-org/Contractner/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://agilelab-org/Contractner/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/agilelab-org/Contractner/resolve/main/special_tokens_map.json
286 Bytes
- Xet hash:
- 4c423d782078a670c9df8fb9072b6f6fcdb29bc62ccb1edc911c52b5fbd03775
- Size of remote file:
- 286 Bytes
- SHA256:
- 9463f61e1b109a8eb4688b829260d7c6b1e6dff04c98ff7269bb89e2b92369b9
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