Instructions to use urchade/gliner_multi-v2.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use urchade/gliner_multi-v2.1 with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("urchade/gliner_multi-v2.1") 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
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README.md
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datasets:
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- urchade/pile-mistral-v0.1
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pipeline_tag: token-classification
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datasets:
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- urchade/pile-mistral-v0.1
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pipeline_tag: token-classification
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```
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CrossNER_AI : 51.6%
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CrossNER_literature : 61.6%
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CrossNER_music : 66.5%
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CrossNER_politics : 70.0%
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CrossNER_science : 61.6%
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mit-movie : 44.4%
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mit-restaurant : 29.0%
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Average : 55.0%
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```
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