Update README.md

README.md

@@ -116,19 +116,21 @@ This is a copy of the dataset uploaded on Hugging Face for easy access. The orig
 ```python
 # usage
 from datasets import load_dataset
-from transformers import CLIPImageProcessor, CLIPTokenizer
+from transformers import CLIPProcessor
 from torch.utils.data import DataLoader
 
-image_processor = CLIPImageProcessor.from_pretrained(clip_path)
-tokenizer = CLIPTokenizer.from_pretrained(clip_path)
+processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32")
 
 def tokenization(example):
-  text_inputs = tokenizer(example["text"], truncation=True, padding=True, return_tensors="pt")
-  image_inputs = image_processor(example["image"], return_tensors="pt")
-  return {'pixel_values': image_inputs['pixel_values'],
-          'input_ids': text_inputs['input_ids'],
-          'attention_mask': text_inputs['attention_mask'],
-          "label": example["label"]}
+    inputs = processor(
+        text=example["text"], images=example["image"], return_tensors="pt"
+    )
+    return {
+        "pixel_values": inputs["pixel_values"],
+        "input_ids": inputs["input_ids"],
+        "attention_mask": inputs["attention_mask"],
+        "label": example["label"],
+    }
 
 dataset = load_dataset('coderchen01/MMSD2.0', 'mmsd-v2')
 dataset.set_transform(tokenization)