Instructions to use DjBROW/run with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DjBROW/run with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="DjBROW/run")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("DjBROW/run") model = AutoModelForTokenClassification.from_pretrained("DjBROW/run", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eaf7868d17cca3d511c84e0c278f357c4843bf295716394ac94414359fba3375
- Size of remote file:
- 5.84 kB
- SHA256:
- 69c710cbbb04a203caa9dbc6e800086e9722453d27b6ef61421482c3ec4aa619
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