Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use kazuma313/emotion_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kazuma313/emotion_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="kazuma313/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("kazuma313/emotion_classification") model = AutoModelForImageClassification.from_pretrained("kazuma313/emotion_classification") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- Feb05_23-01-11_0a17839d1c89
- Feb05_23-17-14_0a17839d1c89
- Feb05_23-24-28_0a17839d1c89
- Feb09_16-54-32_edc91706bab0
- Feb09_17-09-53_edc91706bab0
- Feb09_17-24-19_edc91706bab0
- Feb09_17-36-27_edc91706bab0
- Feb09_17-48-38_edc91706bab0
- Feb09_17-53-16_edc91706bab0
- Feb16_15-11-35_da62d0da9e43
- Feb16_15-21-37_da62d0da9e43