docs: Minor fixes to demo code on README

README.md

@@ -29,10 +29,10 @@ processor = AutoProcessor.from_pretrained("nielsr/layoutxlm-finetuned-xfund-fr")
 model = AutoModelForTokenClassification.from_pretrained(nielsr/layoutxlm-finetuned-xfund-fr")
 
 # assuming you have a French document, turned into an image
-image = Image("...").convert("RGB")
+image = Image.open("...").convert("RGB")
 
 # prepare for the model
-encoding = processor(image, return_offsets_mapping=True, padding="max_length", max_length=512, truncation=True, return_tensors="pt")
+encoding = processor(image, padding="max_length", max_length=512, truncation=True, return_tensors="pt")
 
 with torch.no_grad():
   outputs = model(**encoding)