Instructions to use OttoYu/Image-place with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OttoYu/Image-place with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="OttoYu/Image-place") 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("OttoYu/Image-place") model = AutoModelForImageClassification.from_pretrained("OttoYu/Image-place") - Notebooks
- Google Colab
- Kaggle
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README.md
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tags:
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- vision
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- image-classification
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widget:
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example_title: Teapot
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg
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example_title: Palace
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## Validation Metrics
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tags:
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- vision
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- image-classification
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widget:
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example_title: Teapot
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg
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example_title: Palace
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datasets:
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- OttoYu/im-place-data
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## Validation Metrics
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