Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use jayanta/google-vit-base-patch16-224-cartoon-emotion-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jayanta/google-vit-base-patch16-224-cartoon-emotion-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jayanta/google-vit-base-patch16-224-cartoon-emotion-detection") 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("jayanta/google-vit-base-patch16-224-cartoon-emotion-detection") model = AutoModelForImageClassification.from_pretrained("jayanta/google-vit-base-patch16-224-cartoon-emotion-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jayanta/google-vit-base-patch16-224-cartoon-emotion-detection: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/jayanta/google-vit-base-patch16-224-cartoon-emotion-detection/resolve/main/training_args.bin
- Command line
-
hf download hf://jayanta/google-vit-base-patch16-224-cartoon-emotion-detection/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jayanta/google-vit-base-patch16-224-cartoon-emotion-detection/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- 16028b6afa06ab2c5347518f78f0ee838f271457c3872e3c9640da6384a83af5
- Size of remote file:
- 3.52 kB
- SHA256:
- 7367aabf389f10e9baf68055c00e995dee998629b65aced8504844750d151277
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