FastChat VS MiniGPT-4

gpt2-chatbot isn't the only "mystery model" on LMSYS. Another is "deluxe-chat".

When asked about it in October last year, LMSYS replied [0] "It is an experiment we are running currently. More details will be revealed later"

One distinguishing feature of "deluxe-chat": although it gives high quality answers, it is very slow, so slow that the arena displays a warning whenever it is invoked

[0] https://github.com/lm-sys/FastChat/issues/2527

FastChat

How does it compare with something like FastChat? https://github.com/lm-sys/FastChat

Feature set seems like a decent amount of overlap. One limitation of FastChat, as far as I can tell, is that one is limited to the models that FastChat supports (though I think it would be minor to modify it to support arbitrary models?)

Looks like the Vicuna repo is Apache 2.0 also[1].

What's the interpretation of copyright law that would prevent the code being Apache 2.0 based on the source of the fine-tuning dataset?

[1] https://github.com/lm-sys/FastChat

Check how to start with FastChat. Support FastChat on GitHub ⭐

For something a little heavier but much more robust in terms of features/functionality I've been enjoying FastChat: https://github.com/lm-sys/FastChat

It allows you to plug in different backends so that you can use OpenAI compatible clients with various LLM's, selfhosted or otherwise.

I just think the tech has been out for so long it's not as big of a deal. Mini-Gpt4 has been out for 6 months! Of course the descriptions aren't exactly gpt-4 grade, but with mistral 7b being used as the language model instead of llama 7b, the reasoning ability will improve noticeably.

[1] https://github.com/Vision-CAIR/MiniGPT-4

Isn't there only two open multimodal LLMs, LLaVA and mini-gpt4?

For LLM visual instruction, you can use LLaVA, LaVIN, or MiniGPT-4.

Please read the rules before posting. If you want a model for visual instruction, use LLaVA, LaVIN, or MiniGPT-4.

So we use MiniGPT-4 for image parsing, and yep it does return a pretty detailed (albeit not always accurate) description of the photo. You can actually play around with it on Huggingface here.

We use MiniGPT-4 first to interpret the image and then pass the results onto GPT-4. Hopefully, once GPT-4 makes its multi-modal functionality available, we can do it all in one request.

But I would like to bring up that there are some multi models(llava, miniGPT-4) that are built based on censored llama based models like vicuna. I tried several multi modal models like llava, minigpt4 and blip2. Llava has very good captioning and question answering abilities and it is also much faster than the others(basically real time), though it has some hallucination issue.