Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use hanslab37/emotion_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hanslab37/emotion_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hanslab37/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("hanslab37/emotion_classification") model = AutoModelForImageClassification.from_pretrained("hanslab37/emotion_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c812721c67ece45bcab00639f22b41a2c899ba2de02f5bd0b80cdeff5e5b24d8
- Size of remote file:
- 5.11 kB
- SHA256:
- 76a4fb648aaeec1bbf1b3c19f93d864e40bd9f93cfb0f47a8f4c476298709408
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