Instructions to use flair/ner-multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Flair
How to use flair/ner-multi with Flair:
from flair.data import Sentence from flair.models import SequenceTagger tagger = SequenceTagger.load("flair/ner-multi") sentence = Sentence("George Washington went to Washington.") tagger.predict(sentence) print(sentence) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from flair/ner-multi: direct link, hf CLI and curl.
- Browser
- Download file 1.72 GB
-
https://huggingface.co/flair/ner-multi/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://flair/ner-multi/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/flair/ner-multi/resolve/main/pytorch_model.bin
1.72 GB
- Xet hash:
- aff3e3077843d94664ac710d9cef596e3482c3aedc51524761413f40ff745ef6
- Size of remote file:
- 1.72 GB
- SHA256:
- 9e73a46f5156d8602bde5c1d0d60e658e0dc00339949ca3dfcada6188f28678c
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