Instructions to use robosapiens/class-room with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use robosapiens/class-room with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="robosapiens/class-room") 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("robosapiens/class-room") model = AutoModelForImageClassification.from_pretrained("robosapiens/class-room") - Notebooks
- Google Colab
- Kaggle
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value: 0.8288288116455078
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---
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# class-room
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## Example Images
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#### bathroom
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#### bedroom
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#### dining room
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#### kitchen
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#### living room
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- name: Accuracy
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type: accuracy
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value: 0.8288288116455078
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