Instructions to use jhoppanne/Emotion-Image-Classification-V4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jhoppanne/Emotion-Image-Classification-V4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jhoppanne/Emotion-Image-Classification-V4") 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("jhoppanne/Emotion-Image-Classification-V4") model = AutoModelForImageClassification.from_pretrained("jhoppanne/Emotion-Image-Classification-V4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jhoppanne/Emotion-Image-Classification-V4: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/jhoppanne/Emotion-Image-Classification-V4/resolve/main/training_args.bin
- Command line
-
hf download hf://jhoppanne/Emotion-Image-Classification-V4/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jhoppanne/Emotion-Image-Classification-V4/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- bdde1eb7427f4999e0b74dfa700e4484d4ec8abd65dfa1ea1fc5699c687b0a53
- Size of remote file:
- 4.73 kB
- SHA256:
- 76d761ec940ee48e909106c1823ebb8a455e5a8b61aa2a5cd3cebb8c26542b07
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