Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use pratapaadii/Emotion_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pratapaadii/Emotion_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="pratapaadii/Emotion_Classifier") 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("pratapaadii/Emotion_Classifier") model = AutoModelForImageClassification.from_pretrained("pratapaadii/Emotion_Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c02200087ce1b13e4697070864ba24defeb9980f15e3b88bb178d10b1e09059
- Size of remote file:
- 343 MB
- SHA256:
- 5c4586c5cce0dc5ca846346c12f47e2344b19cd557bc608545f23551adc6f4e7
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