How to use rafmacalaba/gliner25_agents_v3 with GLiNER2:
from gliner2 import AutoExtractor extractor = AutoExtractor.from_pretrained("rafmacalaba/gliner25_agents_v3") # Extract entities text = "Apple CEO Tim Cook announced iPhone 15 in Cupertino yesterday." result = extractor.extract_entities(text, ["company", "person", "product", "location"]) print(result)
https://huggingface.co/rafmacalaba/gliner25_agents_v3/resolve/main/tokenizer.json
hf download hf://rafmacalaba/gliner25_agents_v3/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/rafmacalaba/gliner25_agents_v3/resolve/main/tokenizer.json
