Token Classification
GLiNER
ONNX
Safetensors
NER
GLiNER
information extraction
encoder
entity recognition
Instructions to use knowledgator/gliner-x-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use knowledgator/gliner-x-base with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("knowledgator/gliner-x-base") 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 tokenizer.json from knowledgator/gliner-x-base: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/knowledgator/gliner-x-base/resolve/main/tokenizer.json
- Command line
-
hf download hf://knowledgator/gliner-x-base/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/knowledgator/gliner-x-base/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- f25b8a523583a8b8623dc9efbde728653276b8f422f5f418e5949053b0eb0fe0
- Size of remote file:
- 16.3 MB
- SHA256:
- 619d3790cf59a0e50afdf04239db19093568fbd8d806963e35d54a8fb71d099c
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