Instructions to use seungwon12/cloud_computing_project with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seungwon12/cloud_computing_project with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="seungwon12/cloud_computing_project")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("seungwon12/cloud_computing_project") model = AutoModelForTokenClassification.from_pretrained("seungwon12/cloud_computing_project", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b6d52682f8ed2f850bbff564577638ce992ada5e1f2f87093be8ce49b390a777
- Size of remote file:
- 501 MB
- SHA256:
- aa045a3425b3f8aada9fd0672034133efa6c63f4c27f041dd8942b8aaf8377e7
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