Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use ruben09/emotion_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ruben09/emotion_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ruben09/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("ruben09/emotion_classification") model = AutoModelForImageClassification.from_pretrained("ruben09/emotion_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3134da6a9974036195f0c61135ee3e13b3565e39f43f8718c20480e75036d3be
- Size of remote file:
- 5.24 kB
- SHA256:
- 6a4c51c0f6192125f8ff489a9db96a1b43fe2f056d74436b2e8db758d501204a
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