Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use yangswei/visual-emotion-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yangswei/visual-emotion-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="yangswei/visual-emotion-classification") 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("yangswei/visual-emotion-classification") model = AutoModelForImageClassification.from_pretrained("yangswei/visual-emotion-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd33a21e8b6b4af05df2a6ba9c1a21938db428d87c1a2cfae19e885d81d747fa
- Size of remote file:
- 4.6 kB
- SHA256:
- e2da1fba9bd31ade2900585638ef19abe6e21d53ad9a207b3aa626a7f6b58fef
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