Image Classification
Transformers
Safetensors
PyTorch
vit
vision
facial-expression-recognition
emotion-detection
Instructions to use SeanHowFun/face-emotion-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SeanHowFun/face-emotion-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="SeanHowFun/face-emotion-detection") 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("SeanHowFun/face-emotion-detection") model = AutoModelForImageClassification.from_pretrained("SeanHowFun/face-emotion-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c2ef3281227f3487fc00cd79db7eb6e5d90bdf112e7b7613bae806abaa5aa71
- Size of remote file:
- 343 MB
- SHA256:
- f2f521ea028f1aff5d6021c4458c32ba56ff7a0edfb40e94cf1ab5bdf05c8da1
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