Instructions to use IoriU/emotion_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IoriU/emotion_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="IoriU/emotion_classifier") 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("IoriU/emotion_classifier") model = AutoModelForImageClassification.from_pretrained("IoriU/emotion_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from IoriU/emotion_classifier: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/IoriU/emotion_classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://IoriU/emotion_classifier/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/IoriU/emotion_classifier/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 3842d576eeee1b79d7430c711e512aae72d7712ad5e2d8a0b098e658af990a5c
- Size of remote file:
- 4.73 kB
- SHA256:
- bf0af2e1e0541bb75a835990b66833a5d644bd05b1bcce1ded74d1b3abc20f89
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