Instructions to use Rajaram1996/FacialEmoRecog with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rajaram1996/FacialEmoRecog with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Rajaram1996/FacialEmoRecog") 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("Rajaram1996/FacialEmoRecog") model = AutoModelForImageClassification.from_pretrained("Rajaram1996/FacialEmoRecog", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e28b72bf826f5b51f6c94bb19dbc7f09ce7807d6b60b908c9ef08f052507d7e
- Size of remote file:
- 343 MB
- SHA256:
- 66e39e730324ea3494d76fe134f30b2bd3190db295d8476d20ace0a82cb7474e
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