Instructions to use dwililiya/emotion_recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dwililiya/emotion_recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dwililiya/emotion_recognition") 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("dwililiya/emotion_recognition") model = AutoModelForImageClassification.from_pretrained("dwililiya/emotion_recognition", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "resize": [224, 224], | |
| "normalize": { | |
| "mean": [0.485, 0.456, 0.406], | |
| "std": [0.229, 0.224, 0.225] | |
| } | |
| } | |