Instructions to use Piro17/finetuned-fer2013-balanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Piro17/finetuned-fer2013-balanced with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Piro17/finetuned-fer2013-balanced") 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("Piro17/finetuned-fer2013-balanced") model = AutoModelForImageClassification.from_pretrained("Piro17/finetuned-fer2013-balanced", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f23ad24eef4dcfb52343fb4f1eb553595537cf67dbe70b52f009ee14eecd3609
- Size of remote file:
- 343 MB
- SHA256:
- 51751a1c39c12819f942fc9af26477969285419ab3ede695d6835bf0ca44d282
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