Instructions to use chris32/living-spaces-classification_scraper_balanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chris32/living-spaces-classification_scraper_balanced with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="chris32/living-spaces-classification_scraper_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("chris32/living-spaces-classification_scraper_balanced") model = AutoModelForImageClassification.from_pretrained("chris32/living-spaces-classification_scraper_balanced") - Notebooks
- Google Colab
- Kaggle
- Downloads last month
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Evaluation results
- Accuracyself-reported0.965