Instructions to use Ganaa614/deit-tiny-distilled-patch16-224emotion_model_6feats_big with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ganaa614/deit-tiny-distilled-patch16-224emotion_model_6feats_big with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Ganaa614/deit-tiny-distilled-patch16-224emotion_model_6feats_big") 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("Ganaa614/deit-tiny-distilled-patch16-224emotion_model_6feats_big") model = AutoModelForImageClassification.from_pretrained("Ganaa614/deit-tiny-distilled-patch16-224emotion_model_6feats_big", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bce2db12d9f34ae8b2dc1dee172066acb974f94721ed9607943d974e71ed4a0e
- Size of remote file:
- 5.91 kB
- SHA256:
- 675c20c79d8e2b797dd2d8a998cc76d4cd7857ecd76379031e4400b20d6c461f
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