Instructions to use jhoppanne/Emotion-Image-Classification-V3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jhoppanne/Emotion-Image-Classification-V3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jhoppanne/Emotion-Image-Classification-V3") 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("jhoppanne/Emotion-Image-Classification-V3") model = AutoModelForImageClassification.from_pretrained("jhoppanne/Emotion-Image-Classification-V3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad08b84beb2e3b86aad701c20f46d593a0f3b3d83375ead82028ac4b7b0daf34
- Size of remote file:
- 343 MB
- SHA256:
- 0690d2470676a42f953025a8e32b3c980710ea47735a0527bcd54570e288636b
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