Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use harriskr14/emotion-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harriskr14/emotion-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="harriskr14/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("harriskr14/emotion-classification") model = AutoModelForImageClassification.from_pretrained("harriskr14/emotion-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc3d6c9f4b20c3878b03697a0eca45c0707e975a6b03511c9f8bca9054e8d726
- Size of remote file:
- 5.78 kB
- SHA256:
- bbedeceb4164a11deeb4bd3afa40d93237ed74505915f8cf8874f72d58fe50c0
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