Instructions to use hanphilc/emotion-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hanphilc/emotion-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hanphilc/emotion-detector") 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("hanphilc/emotion-detector") model = AutoModelForImageClassification.from_pretrained("hanphilc/emotion-detector") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 088e09104617a265837a4f8e67816f49f39fcd6edfedede386baeb0e1c87637c
- Size of remote file:
- 5.2 kB
- SHA256:
- 912fad5346a98e013adce19d9d12720e53018c3f5975de008502e1de7c594914
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