Instructions to use aeth0r/cat2vec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aeth0r/cat2vec with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="aeth0r/cat2vec")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("aeth0r/cat2vec") model = AutoModel.from_pretrained("aeth0r/cat2vec") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -22,7 +22,7 @@ dataset = load_dataset("huggingface/cats-image")
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image = dataset["test"]["image"][:2]
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processor = AutoImageProcessor.from_pretrained("microsoft/resnet-50")
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model = ResNetModel.from_pretrained("
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inputs = processor(image, return_tensors="pt")
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image = dataset["test"]["image"][:2]
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processor = AutoImageProcessor.from_pretrained("microsoft/resnet-50")
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model = ResNetModel.from_pretrained("aeth0r/cat2vec")
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inputs = processor(image, return_tensors="pt")
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