Instructions to use Nopphakorn/FER_Mobile_ViT_XXS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nopphakorn/FER_Mobile_ViT_XXS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Nopphakorn/FER_Mobile_ViT_XXS") 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("Nopphakorn/FER_Mobile_ViT_XXS") model = AutoModelForImageClassification.from_pretrained("Nopphakorn/FER_Mobile_ViT_XXS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Nopphakorn/FER_Mobile_ViT_XXS: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/Nopphakorn/FER_Mobile_ViT_XXS/resolve/main/training_args.bin
- Command line
-
hf download hf://Nopphakorn/FER_Mobile_ViT_XXS/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Nopphakorn/FER_Mobile_ViT_XXS/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 70d1739861bfccb628fedc89f9c78c66286e0ce0eceb79217f67251b33e19e07
- Size of remote file:
- 5.11 kB
- SHA256:
- 05a22aed6328a6a879a2cbb9e88b64871ebe91ff2d23c36a4dd415a9454d795a
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