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:
- fbf32bdbb67b0b80a86364f60da609c6d4d68a0777da1ae24a54675a7eaeed17
- Size of remote file:
- 4.73 kB
- SHA256:
- 1cf7a1f53533357c8353203153dcd0a640c927623caa95958acb69b37c5a650e
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