From 13dc6b0853c3cb54e79b18105c0528bc9e84881c Mon Sep 17 00:00:00 2001 From: Francisco Kurucz Date: Mon, 5 Aug 2024 19:14:50 -0300 Subject: [PATCH] Fix documentation links and code reference to model llava-next (#32434) --- docs/source/en/model_doc/llava_next.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/source/en/model_doc/llava_next.md b/docs/source/en/model_doc/llava_next.md index 0c25ed32db..d0558be764 100644 --- a/docs/source/en/model_doc/llava_next.md +++ b/docs/source/en/model_doc/llava_next.md @@ -55,12 +55,12 @@ The original code can be found [here](https://github.com/haotian-liu/LLaVA/tree/ - Note that each checkpoint has been trained with a specific prompt format, depending on which large language model (LLM) was used. You can use the processor's `apply_chat_template` to format your prompts correctly. For that you have to construct a conversation history, passing 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. Below is an example of how to do that and the list of formats accepted by each checkpoint. -We will use [llava-v1.6-mistral-7b-hf](https://huggingface.co/llava-hf/llava-hf/llava-v1.6-mistral-7b-hf) and a conversation history of text and image. Each content field has to be a list of dicts, as follows: +We will use [llava-v1.6-mistral-7b-hf](https://huggingface.co/llava-hf/llava-v1.6-mistral-7b-hf) and a conversation history of text and image. Each content field has to be a list of dicts, as follows: ```python from transformers import LlavaNextProcessor -processor = LlavaNextProcessor.from_pretrained("llava-hf/llava-hf/llava-v1.6-mistral-7b-hf") +processor = LlavaNextProcessor.from_pretrained("llava-hf/llava-v1.6-mistral-7b-hf") conversation = [ {