Instructions to use kargaranamir/Hengam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SpanMarker
How to use kargaranamir/Hengam with SpanMarker:
from span_marker import SpanMarkerModel model = SpanMarkerModel.from_pretrained("kargaranamir/Hengam") entities = model.predict("Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris.") print(entities) - Notebooks
- Google Colab
- Kaggle
Download config.json from kargaranamir/Hengam: direct link, hf CLI and curl.
- Browser
- Download file 57 Bytes
-
https://huggingface.co/kargaranamir/Hengam/resolve/main/config.json
- Command line
-
hf download hf://kargaranamir/Hengam/config.json
-
curl -L -o config.json https://huggingface.co/kargaranamir/Hengam/resolve/main/config.json
57 Bytes
Invalid JSON:Unexpected token ''', ..."S_TABLE":['B-TIM', '"... is not valid JSON
| {"TAGS_TABLE":['B-TIM', 'I-TIM', 'B-DAT', 'I-DAT', 'O']} | |