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:
- 00790fc954ffa94f3d7680b56ba16f34b03640138cf236273d2a23e72aebe81b
- Size of remote file:
- 3.58 kB
- SHA256:
- ba8fee65ada9d98286cd1ea8e150aa5d476854b8d1f9fb10e89e2310694224ff
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