Instructions to use miittnnss/happy-or-sad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use miittnnss/happy-or-sad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="miittnnss/happy-or-sad") 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("miittnnss/happy-or-sad") model = AutoModelForImageClassification.from_pretrained("miittnnss/happy-or-sad") - Notebooks
- Google Colab
- Kaggle
happy-or-sad
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
happy
sad
- Downloads last month
- 6
Evaluation results
- Accuracyself-reported0.800

