Instructions to use RickyIG/emotion_face_image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RickyIG/emotion_face_image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="RickyIG/emotion_face_image_classification") 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("RickyIG/emotion_face_image_classification") model = AutoModelForImageClassification.from_pretrained("RickyIG/emotion_face_image_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d94cd3c19b338332b2170063e54dca714b9cdc3392c0b29eea2ba73a1a50d766
- Size of remote file:
- 343 MB
- SHA256:
- c032fef314f486029a627889f56de73f06eae336446b1dc980d38315aa3f9cfd
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