Image Classification
Transformers
PyTorch
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use dennisjooo/emotion_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dennisjooo/emotion_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dennisjooo/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("dennisjooo/emotion_classification") model = AutoModelForImageClassification.from_pretrained("dennisjooo/emotion_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9262e84cef98a07dd23a7ba1c1bae3c7a0ea4409297c0b830d1e8c6aee000571
- Size of remote file:
- 343 MB
- SHA256:
- d47386f85e768a6b9efa1425abcae2b77949da9199600fa03f685fc80754d8d2
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