Instructions to use agent593/content with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agent593/content with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="agent593/content") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("agent593/content") model = AutoModelForImageClassification.from_pretrained("agent593/content") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c17d92c9d76810a19e51dc466f16b96dd236b5b5fbf2b77fe8c6937feba7d2af
- Size of remote file:
- 343 MB
- SHA256:
- 56c71af11ec564c48f4992a1437b53bcbb175b1fb9b4867d08ccfff1c7cd001e
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