Update README.md

README.md

@@ -25,17 +25,25 @@ It achieves the following results on the evaluation set:
 This model is an experimental model that predicts danbooru tags of images.
 
 ## Example
+
+### Use a pipeline
+
 ```py
 from transformers import pipeline
-pipe = pipeline("image-classification",model="p1atdev/siglip-tagger-test-3",revision="refs/pr/2",trust_remote_code=True)
-pipe("image.jpg", # takes str(path) or numpy array or PIL images as input
- threshold=0.5, #optional parameter defaults to 0
- return_scores = False #optional parameter defaults to False
- )
+
+pipe = pipeline("image-classification", model="p1atdev/siglip-tagger-test-3", trust_remote_code=True)
+pipe(
+ "image.jpg", # takes str(path) or numpy array or PIL images as input
+ threshold=0.5, #optional parameter defaults to 0
+ return_scores = False #optional parameter defaults to False
+)
 ```
+
 * `threshold`: confidence intervale, if it's specified, the pipeline will only return tags with a confidence >= threshold
 * `return_scores`: if specified the pipeline will return the labels and their confidences in a dictionary format.
 
+### Load model directly
+
 ```py
 from PIL import Image
 import torch