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For multimodal models, we need to change the user/assistant roles and add the proper start and end tokens
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Problem
Using the standard Llava15ChatHandler with multimodal Gemma models fail.
Gemma models expect <start_of_turn>user / <start_of_turn>model / <end_of_turn> tokens instead. There is no vision-capable handler subclass for Gemma models, even though the library already follows the pattern of subclassing Llava15ChatHandler for other model families (e.g., ObsidianChatHandler, MoondreamChatHandler, Llava16ChatHandler) in llama_chat_format.py.
Although there is a format_gemma for text based Gemma models, this is bypassed by the chat handler
Solution
For multimodal models, we need to change the user/assistant roles and add the proper start and end tokens using a GemmaChatHandler