Instructions to use ThankGod/vit-base-aiornot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThankGod/vit-base-aiornot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ThankGod/vit-base-aiornot") 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("ThankGod/vit-base-aiornot") model = AutoModelForImageClassification.from_pretrained("ThankGod/vit-base-aiornot", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a82d3eec64f795da267ce98223c543aa22eef2b84fd7e0f21a9c57b2371e8ef
- Size of remote file:
- 343 MB
- SHA256:
- bc653aae71662e372d334a41911bff9bbaf6af849e24e3859433bc8a619a627d
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