

prompts = [
     [   "https://images.unsplash.com/photo-1543349689-9a4d426bee8e?ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D&auto=format&fit=crop&w=3501&q=80",
         "This is an image of ",
     ],
     [   "https://images.unsplash.com/photo-1623944889288-cd147dbb517c?ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D&auto=format&fit=crop&w=3540&q=80",
         "This is an image of ",
     ],
     [   "https://images.unsplash.com/photo-1471193945509-9ad0617afabf?ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D&auto=format&fit=crop&w=3540&q=80",
         "This is an image of ",
     ],
 ]
inputs = processor(prompts, return_tensors="pt").to("cuda")
bad_words_ids = processor.tokenizer(["", ""], add_special_tokens=False).input_ids
generated_ids = model.generate(**inputs, max_new_tokens=10, bad_words_ids=bad_words_ids)
generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)
for i,t in enumerate(generated_text):
     print(f"{i}:\n{t}\n") 
0:
This is an image of the Eiffel Tower in Paris, France.