Llava: add default chat templates (#31691)

* add default chat templates

* Update src/transformers/models/llava/processing_llava.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/models/llava_next/processing_llava_next.py

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* more clear docstring and docs

* Update docs/source/en/model_doc/llava.md

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update docs/source/en/model_doc/llava_next.md

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update docs/source/en/model_doc/vipllava.md

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* add tests

* remove default templates (see #31733)

* load chat template from another file

* Update docs/source/en/model_doc/llava_next.md

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* revert some changes in docs

* forgot vipllava

* chat template file is not temporary hack

* warn if loading from processor

* not that file

* similarly modify `save_pretrained`

* Update tests/models/llava_next/test_processor_llava_next.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update tests/models/vipllava/test_processor_vipllava.py

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* Update docs/source/en/model_doc/vipllava.md

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* Update src/transformers/processing_utils.py

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* Update src/transformers/processing_utils.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update docs/source/en/model_doc/vipllava.md

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update docs/source/en/model_doc/llava.md

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update docs/source/en/model_doc/llava.md

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update docs/source/en/model_doc/llava_next.md

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update docs/source/en/model_doc/llava_next.md

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/processing_utils.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update docs/source/en/model_doc/llava_next.md

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* fix

---------

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

docs/source/en/model_doc/llava.md

@@ -40,7 +40,42 @@ The original code can be found [here](https://github.com/haotian-liu/LLaVA/tree/
 
 - Note the model has not been explicitly trained to process multiple images in the same prompt, although this is technically possible, you may experience inaccurate results.
 
-- For better results, we recommend users to prompt the model with the correct prompt format. Below is a list of prompt formats accepted by each llava checkpoint:
+- For better results, we recommend users to use the processor's `apply_chat_template()` method to format your prompt correctly. For that you need to construct a conversation history, passing in a plain string will not format your prompt. Each message in the conversation history for chat templates is a dictionary with keys "role" and "content". The "content" should be a list of dictionaries, for "text" and "image" modalities, as follows:
+
+```python
+from transformers import AutoProcessor
+
+processor = AutoProcessor.from_pretrained("llava-hf/llava-1.5-7b-hf")
+
+conversation = [
+    {
+        "role": "user",
+        "content": [
+            {"type": "image"},
+            {"type": "text", "text": "What’s shown in this image?"},
+            ],
+    },
+    {
+        "role": "assistant",
+        "content": [{"type": "text", "text": "This image shows a red stop sign."},]
+    },
+    {
+
+        "role": "user",
+        "content": [
+            {"type": "text", "text": "Describe the image in more details."},
+        ],
+    },
+]
+
+text_prompt = processor.apply_chat_template(conversation, add_generation_prompt=True)
+
+# Note that the template simply formats your prompt, you still have to tokenize it and obtain pixel values for your images
+print(text_prompt)
+>>> "USER: <image>\n<What’s shown in this image? ASSISTANT: This image shows a red stop sign.</s>USER: Describe the image in more details. ASSISTANT:"
+```
+
+- If you want to construct a chat prompt yourself, below is a list of prompt formats accepted by each llava checkpoint:
 
 [llava-interleave models](https://huggingface.co/collections/llava-hf/llava-interleave-668e19a97da0036aad4a2f19) requires the following format:
 ```bash
@@ -64,6 +99,7 @@ For multiple turns conversation:
 "USER: <image>\n<prompt1> ASSISTANT: <answer1></s>USER: <prompt2> ASSISTANT: <answer2></s>USER: <prompt3> ASSISTANT:"
 ```
 
+
 ### Using Flash Attention 2
 
 Flash Attention 2 is an even faster, optimized version of the previous optimization, please refer to the [Flash Attention 2 section of performance docs](https://huggingface.co/docs/transformers/perf_infer_gpu_one).