Instructions to use NabeelShar/emotion-dectect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NabeelShar/emotion-dectect with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="NabeelShar/emotion-dectect") 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("NabeelShar/emotion-dectect") model = AutoModelForImageClassification.from_pretrained("NabeelShar/emotion-dectect", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 726c6bd2ff24ff58692e946540713836c1a15833e2ddf61974abf604547957f0
- Size of remote file:
- 343 MB
- SHA256:
- 18035e54e0e275c3715e720560bc3565ca6e888b15a76bf06d5479d62e779226
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