From e8f8d2042ccdb5867b1e4e20400d8cfb206ae721 Mon Sep 17 00:00:00 2001 From: Niels Rogge Date: Mon, 27 Feb 2023 15:07:09 +0000 Subject: [PATCH] Update README.md --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 592cd7a..e72576c 100644 --- a/README.md +++ b/README.md @@ -31,17 +31,17 @@ fine-tuned versions on a task that interests you. Here is how to use this model to classify an image of the COCO 2017 dataset into one of the 1,000 ImageNet classes: ```python -from transformers import AutoFeatureExtractor, ResNetForImageClassification +from transformers import AutoImageProcessor, ResNetForImageClassification import torch from datasets import load_dataset dataset = load_dataset("huggingface/cats-image") image = dataset["test"]["image"][0] -feature_extractor = AutoFeatureExtractor.from_pretrained("microsoft/resnet-50") +processor = AutoImageProcessor.from_pretrained("microsoft/resnet-50") model = ResNetForImageClassification.from_pretrained("microsoft/resnet-50") -inputs = feature_extractor(image, return_tensors="pt") +inputs = processor(image, return_tensors="pt") with torch.no_grad(): logits = model(**inputs).logits