Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
vit
huggingpics
Eval Results (legacy)
Instructions to use gaurang11/behavior with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gaurang11/behavior with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="gaurang11/behavior") 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("gaurang11/behavior") model = AutoModelForImageClassification.from_pretrained("gaurang11/behavior") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("gaurang11/behavior")
model = AutoModelForImageClassification.from_pretrained("gaurang11/behavior")Quick Links
behavior
Autogenerated by HuggingPics🤗🖼️
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.
Example Images
anger
disgust
fear
happiness
neutrality
sadness
surprise
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Evaluation results
- Accuracyself-reported0.571







# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="gaurang11/behavior") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")