Instructions to use mo-thecreator/vit-Facial-Expression-Recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mo-thecreator/vit-Facial-Expression-Recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mo-thecreator/vit-Facial-Expression-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("mo-thecreator/vit-Facial-Expression-Recognition") model = AutoModelForImageClassification.from_pretrained("mo-thecreator/vit-Facial-Expression-Recognition", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 141f88fa7f4a1bf95a1ddca4d935bbaeb28bf7052673cb1dfe34980c379f5135
- Size of remote file:
- 4.28 kB
- SHA256:
- 4c9a73d6a47b33bc9e87842bbfdec20df6b4e2f468a87ece2e28ea57383c1be2
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