Instructions to use Aziracrow/Crowley with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Flair
How to use Aziracrow/Crowley with Flair:
from flair.data import Sentence from flair.models import SequenceTagger tagger = SequenceTagger.load("Aziracrow/Crowley") sentence = Sentence("George Washington went to Washington.") tagger.predict(sentence) print(sentence) - Notebooks
- Google Colab
- Kaggle
|
Download README.md from Aziracrow/Crowley: direct link, hf CLI and curl.
- Browser
- Download file 146 Bytes
-
https://huggingface.co/Aziracrow/Crowley/resolve/refs%2Fpr%2F1/README.md
- Command line
-
hf download hf://Aziracrow/Crowley@refs/pr/1/README.md
-
curl -L -H "Authorization: Bearer $HF_TOKEN" -o README.md https://huggingface.co/Aziracrow/Crowley/resolve/refs%2Fpr%2F1/README.md
146 Bytes
| license: openrail | |
| datasets: | |
| - HuggingFaceTB/cosmopedia | |
| metrics: | |
| - character | |
| library_name: flair | |
| pipeline_tag: audio-to-audio | |
| tags: | |
| - legal | |