📰 Update about.md

packages/tasks/src/tasks/image-classification/about.md

@@ -16,12 +16,14 @@ With the `transformers` library, you can use the `image-classification` pipeline
 
 ```python
 from transformers import pipeline
-clf = pipeline("image-classification")
-clf("path_to_a_cat_image")
-
-[{'label': 'tabby cat', 'score': 0.731},
-...
-]
+image_classifier = pipeline(task="image-classification", model="microsoft/resnet-50")
+image_classifier("path_to_a_cat_image")
+
+[{'label': 'Egyptian cat', 'score': 0.7005051970481873},
+ {'label': 'tabby, tabby cat', 'score': 0.16163259744644165},
+ {'label': 'tiger cat', 'score': 0.04507654905319214},
+ {'label': 'lynx, catamount', 'score': 0.011848953552544117},
+ {'label': 'bucket, pail', 'score': 0.009444382973015308}]
 ```
 
 You can use [huggingface.js](https://github.com/huggingface/huggingface.js) to classify images using models on Hugging Face Hub.