Instructions to use mm-ai/vit-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mm-ai/vit-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mm-ai/vit-model") 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("mm-ai/vit-model") model = AutoModelForImageClassification.from_pretrained("mm-ai/vit-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d8537fc8dc6eca2098ae675614199f03821602ad29975e5c4c4b08d5f9eeac3
- Size of remote file:
- 344 MB
- SHA256:
- 2c148c817a39d872d20fd94a358bf3222b396769407f0f04986499003e5c3280
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