Instructions to use RickyIG/emotion_face_image_classification_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RickyIG/emotion_face_image_classification_v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="RickyIG/emotion_face_image_classification_v3") 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("RickyIG/emotion_face_image_classification_v3") model = AutoModelForImageClassification.from_pretrained("RickyIG/emotion_face_image_classification_v3") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:7831fb743f96fb9581e298c9941708d582a6a10c200d3d2ebb33848e6a50d3a5
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size 343242432
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