Instructions to use ayooke97/emotion_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ayooke97/emotion_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ayooke97/emotion_classifier") 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("ayooke97/emotion_classifier") model = AutoModelForImageClassification.from_pretrained("ayooke97/emotion_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e106fa0adb8ed73d687d13f41c83b49538a4afa762960e3306cc5e52b826a4ff
- Size of remote file:
- 5.37 kB
- SHA256:
- 62485ef4b039dcdbf86f12c7a4555bf558c3b15b193e2a9bce4f35b997cda59a
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