fix

src/transformers/models/idefics2/modeling_idefics2.py

@@ -1786,17 +1786,13 @@ def forward(
         >>> from transformers import AutoProcessor, AutoModelForVision2Seq
         >>> from transformers.image_utils import load_image
 
-        >>> DEVICE = "cuda:0"
-
         >>> # Note that passing the image urls (instead of the actual pil images) to the processor is also possible
         >>> image1 = load_image("https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg")
         >>> image2 = load_image("https://cdn.britannica.com/59/94459-050-DBA42467/Skyline-Chicago.jpg")
         >>> image3 = load_image("https://cdn.britannica.com/68/170868-050-8DDE8263/Golden-Gate-Bridge-San-Francisco.jpg")
 
         >>> processor = AutoProcessor.from_pretrained("HuggingFaceM4/idefics2-8b-base")
-        >>> model = AutoModelForVision2Seq.from_pretrained(
-        ...     "HuggingFaceM4/idefics2-8b-base",
-        ... ).to(DEVICE)
+        >>> model = AutoModelForVision2Seq.from_pretrained("HuggingFaceM4/idefics2-8b-base", device_map="auto")
 
         >>> BAD_WORDS_IDS = processor.tokenizer(["<image>", "<fake_token_around_image>"], add_special_tokens=False).input_ids
         >>> EOS_WORDS_IDS = [processor.tokenizer.eos_token_id]
@@ -1807,13 +1803,14 @@ def forward(
         ...   "In which city is that bridge located?<image>",
         >>> ]
         >>> images = [[image1, image2], [image3]]
-        >>> inputs = processor(text=prompts, padding=True, return_tensors="pt").to(DEVICE)
+        >>> inputs = processor(text=prompts, padding=True, return_tensors="pt").to("cuda")
 
         >>> # Generate
-        >>> generated_ids = model.generate(**inputs, bad_words_ids=BAD_WORDS_IDS, max_new_tokens=500)
+        >>> generated_ids = model.generate(**inputs, bad_words_ids=BAD_WORDS_IDS, max_new_tokens=20)
         >>> generated_texts = processor.batch_decode(generated_ids, skip_special_tokens=True)
 
         >>> print(generated_texts)
+        ['In this image, we can see the city of New York, and more specifically the Statue of Liberty. In this image, we can see the city of New York, and more specifically the Statue of Liberty.\n\n', 'In which city is that bridge located?\n\nThe bridge is located in the city of Pittsburgh, Pennsylvania.\n\n\nThe bridge is']
         ```"""
 
         output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions