fix input

pipeline.py

@@ -26,7 +26,7 @@ class PreTrainedPipeline():
                 - "feature_vector": A list of floats corresponding to the image embedding.
         """
 
-        batch_dict = self.tokenizer(inputs, max_length=512,
+        batch_dict = self.tokenizer([inputs], max_length=512,
                                     padding=True, truncation=True, return_tensors='pt')
         with torch.no_grad():
             outputs = self.model(**batch_dict)