Instructions to use mostafasmart/vit-base-patch16-224-2class_normal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mostafasmart/vit-base-patch16-224-2class_normal with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mostafasmart/vit-base-patch16-224-2class_normal") 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("mostafasmart/vit-base-patch16-224-2class_normal") model = AutoModelForImageClassification.from_pretrained("mostafasmart/vit-base-patch16-224-2class_normal", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from mostafasmart/vit-base-patch16-224-2class_normal: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/mostafasmart/vit-base-patch16-224-2class_normal/resolve/main/tf_model.h5
- Command line
-
hf download hf://mostafasmart/vit-base-patch16-224-2class_normal/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/mostafasmart/vit-base-patch16-224-2class_normal/resolve/main/tf_model.h5
343 MB
- Xet hash:
- 42758e943d1f6993831126f3727b24448c42ce0875710f08a7db0c5d908beae4
- Size of remote file:
- 343 MB
- SHA256:
- 5ba04ce1b579653ab2e8875c6b365e041bee4e3ebd4bd4a7abdceeb700f7042d
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