Instructions to use ghaith1997/butler-annotations with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghaith1997/butler-annotations with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ghaith1997/butler-annotations")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("ghaith1997/butler-annotations") model = AutoModelForTokenClassification.from_pretrained("ghaith1997/butler-annotations", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2008158be822f3b9a703d2095d1d5bb4cd3db44ad0855c72bb01c3ec76617f00
- Size of remote file:
- 504 MB
- SHA256:
- 9a6db804d43c916ee6bdf61230f668b82a607f3cad81c76499223661990d62ef
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