Instructions to use jcmeyer/week8hw_model1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jcmeyer/week8hw_model1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="jcmeyer/week8hw_model1")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("jcmeyer/week8hw_model1") model = AutoModel.from_pretrained("jcmeyer/week8hw_model1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 013205711540ff1c0872614a78989e664f8e38bc1f5aa46b25b00864a1d2cd5b
- Size of remote file:
- 166 MB
- SHA256:
- b079ea5055bc2a980ffc50cc9fffa470b7a4ff86f10700d9a52c49506cd258aa
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