Instructions to use anggtpd/emotion_recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anggtpd/emotion_recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="anggtpd/emotion_recognition") 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("anggtpd/emotion_recognition") model = AutoModelForImageClassification.from_pretrained("anggtpd/emotion_recognition") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5329a2edbbaf4fcfba667e83c611d14bcda85832b7e6acbfbe6fa501411ec200
- Size of remote file:
- 343 MB
- SHA256:
- fe66e0a84467c3897a72f7e4c56f2c5d729550357b49cd482ac0602d3160934c
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