Instructions to use bryanzhou008/vit-base-patch16-224-in21k-finetuned-inaturalist with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bryanzhou008/vit-base-patch16-224-in21k-finetuned-inaturalist with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="bryanzhou008/vit-base-patch16-224-in21k-finetuned-inaturalist") 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("bryanzhou008/vit-base-patch16-224-in21k-finetuned-inaturalist") model = AutoModelForImageClassification.from_pretrained("bryanzhou008/vit-base-patch16-224-in21k-finetuned-inaturalist", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51400300d88a628297501d0110a22c857a3a6a2c2b819354fccc7c8305b19648
- Size of remote file:
- 343 MB
- SHA256:
- 700541e90f78d50c06a3f9fa223f067c296dcf600091ffe1899b209e3f3d937f
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