Image Classification
Transformers
PyTorch
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use kensvin/emotion_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kensvin/emotion_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="kensvin/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("kensvin/emotion_classification") model = AutoModelForImageClassification.from_pretrained("kensvin/emotion_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5e3eeaff3f4e3334473fc474fbc8d1bd62383c6fc3cec7bf1d8046f5bb54bf9e
- Size of remote file:
- 343 MB
- SHA256:
- 7e105177fae903bf1218cfbf0b76330b3cf10afb4637e72713298e5c0db1fd24
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