Token Classification
SpanMarker
Safetensors
English
ner
named-entity-recognition
generated_from_span_marker_trainer
climate-change
earth-science
Eval Results (legacy)
Instructions to use P0L3/CliReNER-EnvironmentalBERT-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SpanMarker
How to use P0L3/CliReNER-EnvironmentalBERT-base with SpanMarker:
from span_marker import SpanMarkerModel model = SpanMarkerModel.from_pretrained("P0L3/CliReNER-EnvironmentalBERT-base") entities = model.predict("Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris.") print(entities) - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from P0L3/CliReNER-EnvironmentalBERT-base: direct link, hf CLI and curl.
- Browser
- Download file 3.56 MB
-
https://huggingface.co/P0L3/CliReNER-EnvironmentalBERT-base/resolve/main/tokenizer.json
- Command line
-
hf download hf://P0L3/CliReNER-EnvironmentalBERT-base/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/P0L3/CliReNER-EnvironmentalBERT-base/resolve/main/tokenizer.json
3.56 MB
File too large to display, you can check the raw version instead.