Instructions to use vesteinn/vit-mae-inat21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vesteinn/vit-mae-inat21 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="vesteinn/vit-mae-inat21") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("vesteinn/vit-mae-inat21") model = AutoModelForImageClassification.from_pretrained("vesteinn/vit-mae-inat21", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Update README.md
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (5fe8673f0857bb0a54a652b516c51d41411a21e2) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>7596dcb
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