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Update README.md

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@@ -36,17 +36,17 @@ fine-tuned versions on a task that interests you.
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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 ConvNextFeatureExtractor, 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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- feature_extractor = ConvNextFeatureExtractor.from_pretrained("facebook/convnext-base-224-22k")
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  model = ConvNextForImageClassification.from_pretrained("facebook/convnext-base-224-22k")
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- inputs = feature_extractor(image, return_tensors="pt")
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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-base-224-22k")
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  model = ConvNextForImageClassification.from_pretrained("facebook/convnext-base-224-22k")
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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