Instructions to use dima806/facial_emotions_image_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/facial_emotions_image_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dima806/facial_emotions_image_detection") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("dima806/facial_emotions_image_detection") model = AutoModelForImageClassification.from_pretrained("dima806/facial_emotions_image_detection", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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Adding `safetensors` variant of this model (#2)
- Adding `safetensors` variant of this model (293c31733c346dda715f99c9c4c52da49c33ad99) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>0ce8dd0
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