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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78ea044e40009c2739df08c9874be3080eb46b710d4ea8b45b56b9e86fdc5e7e
- Size of remote file:
- 501 MB
- SHA256:
- 07747011805fc25197e0a5330924c8ac89901b4861b3e53187be629d4ce129ea
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