Instructions to use ljvmiranda921/tl_gliner_medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use ljvmiranda921/tl_gliner_medium with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("ljvmiranda921/tl_gliner_medium") 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 spm.model from ljvmiranda921/tl_gliner_medium: direct link, hf CLI and curl.
- Browser
- Download file 2.46 MB
-
https://huggingface.co/ljvmiranda921/tl_gliner_medium/resolve/main/spm.model
- Command line
-
hf download hf://ljvmiranda921/tl_gliner_medium/spm.model
-
curl -L -o spm.model https://huggingface.co/ljvmiranda921/tl_gliner_medium/resolve/main/spm.model
2.46 MB
- Xet hash:
- ceef70ee5c068f2e8ec2ea787d1566d2f5846b612f0e0a3879edffa246dc91cf
- Size of remote file:
- 2.46 MB
- SHA256:
- c679fbf93643d19aab7ee10c0b99e460bdbc02fedf34b92b05af343b4af586fd
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