Instructions to use codewithdark/face-emotion-detect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codewithdark/face-emotion-detect with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="codewithdark/face-emotion-detect") 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("codewithdark/face-emotion-detect") model = AutoModelForImageClassification.from_pretrained("codewithdark/face-emotion-detect", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad4ec18801ae76ded2dcd8a7e63d701c622372d9ba4699d6da3a27ae040988e0
- Size of remote file:
- 343 MB
- SHA256:
- bcd8c2f3f372764686f4cd0ea442de1533bc334d883e4039f198039036e166df
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