Token Classification
GLiNER
ONNX
Safetensors
NER
GLiNER
information extraction
encoder
entity recognition
Instructions to use knowledgator/gliner-x-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use knowledgator/gliner-x-small with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("knowledgator/gliner-x-small") 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 spiece.model from knowledgator/gliner-x-small: direct link, hf CLI and curl.
- Browser
- Download file 4.31 MB
-
https://huggingface.co/knowledgator/gliner-x-small/resolve/main/spiece.model
- Command line
-
hf download hf://knowledgator/gliner-x-small/spiece.model
-
curl -L -o spiece.model https://huggingface.co/knowledgator/gliner-x-small/resolve/main/spiece.model
4.31 MB
- Xet hash:
- c002d43daac2cff8ed238836274d14498980e85c24cfd4076159b27131e91e77
- Size of remote file:
- 4.31 MB
- SHA256:
- ef78f86560d809067d12bac6c09f19a462cb3af3f54d2b8acbba26e1433125d6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.