Update README.md

README.md

@@ -25,7 +25,7 @@ Disclaimer: The team releasing RegNet did not write a model card for this model
 
 ## Model description
 
-The authors trained [RegNets](https://huggingface.co/?models=regnet) models in a self-supervised fashion on bilion of random images from the internet. This model is later finetuned on ImageNet
+The authors trained [RegNets](https://huggingface.co/?models=regnet) models in a self-supervised fashion on a billion uncurated Instagram images. This model is later fine-tuned on ImageNet.
 
 ![model image](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/regnet_architecture.png)
 
@@ -46,8 +46,8 @@ Here is how to use this model:
 >>> dataset = load_dataset("huggingface/cats-image")
 >>> image = dataset["test"]["image"][0]
 
->>> feature_extractor = AutoFeatureExtractor.from_pretrained("zuppif/regnet-y-040")
->>> model = RegNetForImageClassification.from_pretrained("zuppif/regnet-y-040")
+>>> feature_extractor = AutoFeatureExtractor.from_pretrained("facebook/regnet-y-320-seer-in1k")
+>>> model = RegNetForImageClassification.from_pretrained("facebook/regnet-y-320-seer-in1k")
 
 >>> inputs = feature_extractor(image, return_tensors="pt")
 
@@ -60,6 +60,4 @@ Here is how to use this model:
 'tabby, tabby cat'
 ```
 
-
-
 For more code examples, we refer to the [documentation](https://huggingface.co/docs/transformers/master/en/model_doc/regnet).