[docs] Fix image link (huggingface#36869)

* fix image link

* fix

* update

* fix

Author: stevhliu

docs/source/en/processors.md

@@ -29,8 +29,8 @@ import requests
 
 processor = AutoProcessor.from_pretrained("google/paligemma-3b-pt-224")
 
-prompt = "answer en Where is the cow standing?"
-url = "https://huggingface.co/gv-hf/PaliGemma-test-224px-hf/resolve/main/cow_beach_1.png"
+prompt = "answer en Where is the cat standing?"
+url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/pipeline-cat-chonk.jpeg"
 image = Image.open(requests.get(url, stream=True).raw)
 
 inputs = processor(text=prompt, images=image, return_tensors="pt")

src/transformers/models/gemma3/modeling_gemma3.py

@@ -1272,20 +1272,37 @@ def forward(
         >>> import requests
         >>> from transformers import AutoProcessor, Gemma3ForConditionalGeneration
 
-        >>> model = Gemma3ForConditionalGeneration.from_pretrained("google/Gemma3-test-224px-hf")
-        >>> processor = AutoProcessor.from_pretrained("google/Gemma3-test-224px-hf")
-
-        >>> prompt = "answer en Where is the cow standing?"
-        >>> url = "https://huggingface.co/gv-hf/Gemma3-test-224px-hf/resolve/main/cow_beach_1.png"
-        >>> image = Image.open(requests.get(url, stream=True).raw)
-
-        >>> inputs = processor(images=image, text=prompt,  return_tensors="pt")
-
+        >>> model = Gemma3ForConditionalGeneration.from_pretrained("google/gemma-3-4b-it")
+        >>> processor = AutoProcessor.from_pretrained("google/gemma-3-4b-it")
+
+        >>> messages = [
+        ...     {
+        ...         "role": "system",
+        ...         "content": [
+        ...             {"type": "text", "text": "You are a helpful assistant."}
+        ...         ]
+        ...     },
+        ...     {
+        ...         "role": "user", "content": [
+        ...             {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/pipeline-cat-chonk.jpeg"},
+        ...             {"type": "text", "text": "Where is the cat standing?"},
+        ...         ]
+        ...     },
+        ... ]
+
+        >>> inputs = processor.apply_chat_template(
+        ...     messages,
+        ...     tokenizer=True,
+        ...     return_dict=True,
+        ...     return_tensors="pt",
+        ...     add_generation_prompt=True
+        ... )
         >>> # Generate
-        >>> generate_ids = model.generate(**inputs, max_length=30)
+        >>> generate_ids = model.generate(**inputs)
         >>> processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
-        "answer en Where is the cow standing?\nbeach"
-        ```"""
+        "user\nYou are a helpful assistant.\n\n\n\n\n\nWhere is the cat standing?\nmodel\nBased on the image, the cat is standing in a snowy area, likely outdoors. It appears to"
+        ```
+        """
 
         if (input_ids is None) ^ (inputs_embeds is not None):
             raise ValueError("You must specify exactly one of input_ids or inputs_embeds")

src/transformers/models/gemma3/modular_gemma3.py

@@ -883,20 +883,37 @@ def forward(
         >>> import requests
         >>> from transformers import AutoProcessor, Gemma3ForConditionalGeneration
 
-        >>> model = Gemma3ForConditionalGeneration.from_pretrained("google/Gemma3-test-224px-hf")
-        >>> processor = AutoProcessor.from_pretrained("google/Gemma3-test-224px-hf")
-
-        >>> prompt = "answer en Where is the cow standing?"
-        >>> url = "https://huggingface.co/gv-hf/Gemma3-test-224px-hf/resolve/main/cow_beach_1.png"
-        >>> image = Image.open(requests.get(url, stream=True).raw)
-
-        >>> inputs = processor(images=image, text=prompt,  return_tensors="pt")
-
+        >>> model = Gemma3ForConditionalGeneration.from_pretrained("google/gemma-3-4b-it")
+        >>> processor = AutoProcessor.from_pretrained("google/gemma-3-4b-it")
+
+        >>> messages = [
+        ...     {
+        ...         "role": "system",
+        ...         "content": [
+        ...             {"type": "text", "text": "You are a helpful assistant."}
+        ...         ]
+        ...     },
+        ...     {
+        ...         "role": "user", "content": [
+        ...             {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/pipeline-cat-chonk.jpeg"},
+        ...             {"type": "text", "text": "Where is the cat standing?"},
+        ...         ]
+        ...     },
+        ... ]
+
+        >>> inputs = processor.apply_chat_template(
+        ...     messages,
+        ...     tokenizer=True,
+        ...     return_dict=True,
+        ...     return_tensors="pt",
+        ...     add_generation_prompt=True
+        ... )
         >>> # Generate
-        >>> generate_ids = model.generate(**inputs, max_length=30)
+        >>> generate_ids = model.generate(**inputs)
         >>> processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
-        "answer en Where is the cow standing?\nbeach"
-        ```"""
+        "user\nYou are a helpful assistant.\n\n\n\n\n\nWhere is the cat standing?\nmodel\nBased on the image, the cat is standing in a snowy area, likely outdoors. It appears to"
+        ```
+        """
 
         if (input_ids is None) ^ (inputs_embeds is not None):
             raise ValueError("You must specify exactly one of input_ids or inputs_embeds")

src/transformers/models/paligemma/modeling_paligemma.py

@@ -464,19 +464,19 @@ def forward(
         >>> import requests
         >>> from transformers import AutoProcessor, PaliGemmaForConditionalGeneration
 
-        >>> model = PaliGemmaForConditionalGeneration.from_pretrained("google/PaliGemma-test-224px-hf")
-        >>> processor = AutoProcessor.from_pretrained("google/PaliGemma-test-224px-hf")
+        >>> model = PaliGemmaForConditionalGeneration.from_pretrained("google/paligemma2-3b-mix-224")
+        >>> processor = AutoProcessor.from_pretrained("google/paligemma2-3b-mix-224")
 
-        >>> prompt = "answer en Where is the cow standing?"
-        >>> url = "https://huggingface.co/gv-hf/PaliGemma-test-224px-hf/resolve/main/cow_beach_1.png"
+        >>> prompt = "Where is the cat standing?"
+        >>> url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/pipeline-cat-chonk.jpeg"
         >>> image = Image.open(requests.get(url, stream=True).raw)
 
         >>> inputs = processor(images=image, text=prompt,  return_tensors="pt")
 
         >>> # Generate
-        >>> generate_ids = model.generate(**inputs, max_length=30)
+        >>> generate_ids = model.generate(**inputs,)
         >>> processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
-        "answer en Where is the cow standing?\nbeach"
+        "Where is the cat standing?\nsnow"
         ```"""
 
         if (input_ids is None) ^ (inputs_embeds is not None):