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 pytorch_model.bin from agilelab-org/Contractner: direct link, hf CLI and curl.
- Browser
- Download file 1.16 GB
-
https://huggingface.co/agilelab-org/Contractner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://agilelab-org/Contractner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/agilelab-org/Contractner/resolve/main/pytorch_model.bin
1.16 GB
- Xet hash:
- 7a57cc563b9b3a27c7b9f283a426afe6378012e83b92f2643222c07be59ec1f1
- Size of remote file:
- 1.16 GB
- SHA256:
- 2175a73b2be700594661330dbaecb0a2a842aa4ef06e5863a2338d68cc2a0403
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