GLiNER2
Safetensors
extractor
Token Classification
Zero-Shot Classification
Text Classification
relation extraction
Structured extraction
Instructions to use fastino/gliner2-multi-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER2
How to use fastino/gliner2-multi-v1 with GLiNER2:
from gliner2 import GLiNER2 model = GLiNER2.from_pretrained("fastino/gliner2-multi-v1") # Extract entities text = "Apple CEO Tim Cook announced iPhone 15 in Cupertino yesterday." result = extractor.extract_entities(text, ["company", "person", "product", "location"]) print(result) - Notebooks
- Google Colab
- Kaggle
Languages supported and context length?
#2
by abpani1994 - opened
Is GLiNER2βs context length of 2,048 based on the number of tokens processed by gliner.data_processor.words_splitter(), or does it use a normal split(' ') word count?
I can see that the vocab size is 250k does that mean it can support 100+ languages like BGE M3?
abpani1994 changed discussion title from Languages supported to Languages supported?
abpani1994 changed discussion title from Languages supported? to Languages supported and context length?
@abpani1994 , have you found an answer for the first question? (The second is answered here: https://huggingface.co/fastino/gliner2-multi-v1/discussions/1#693ac86818cb030278ed8a4c).