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            Here is how to use this model to classify an image of the COCO 2017 dataset into one of the 1,000 ImageNet classes:
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            ```python
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            from transformers import  | 
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            import torch
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            from datasets import load_dataset
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            dataset = load_dataset("huggingface/cats-image")
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            image = dataset["test"]["image"][0]
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            model = ConvNextForImageClassification.from_pretrained("facebook/convnext-tiny-224")
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            inputs =  | 
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            with torch.no_grad():
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                logits = model(**inputs).logits
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            Here is how to use this model to classify an image of the COCO 2017 dataset into one of the 1,000 ImageNet classes:
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            ```python
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            +
            from transformers import ConvNextImageProcessor, ConvNextForImageClassification
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            import torch
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            from datasets import load_dataset
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            dataset = load_dataset("huggingface/cats-image")
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            image = dataset["test"]["image"][0]
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            processor = ConvNextImageProcessor.from_pretrained("facebook/convnext-tiny-224")
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            model = ConvNextForImageClassification.from_pretrained("facebook/convnext-tiny-224")
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            inputs = processor(image, return_tensors="pt")
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            with torch.no_grad():
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                logits = model(**inputs).logits
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