Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use diwa02/emotion_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use diwa02/emotion_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="diwa02/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("diwa02/emotion_classification") model = AutoModelForImageClassification.from_pretrained("diwa02/emotion_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a1325ef69c7c164053d637885aad107f39e188406a729ec3284ff59353d2b19f
- Size of remote file:
- 5.24 kB
- SHA256:
- 73a53a6a5c8a514d9515ead5c7082783e80b2fa8238f4395e22df017695fca13
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