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:
- 956916c7731a6ccbd28fee70e589a209e641ec5fe2926ae4d45e22409f917d64
- Size of remote file:
- 4.09 kB
- SHA256:
- 9029957fdcde0a238974b4e984f71a3de54b3fe95de332bef21fdb601a6d83bd
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