dalai VS FastChat

I agree, I've definitely seen way more information about running image synthesis models like Stable Diffusion locally than I have LLMs. It's counterintuitive to me that Stable Diffusion takes less RAM than an LLM, especially considering it still needs the word vectors. Goes to show I know nothing.

I guess it comes down to the requirement of a very high end (or multiple) GPU that makes it impractical for most vs just running it in Colab or something.

Tho there are some efforts:

https://github.com/cocktailpeanut/dalai

If you're just looking to play with something locally for the first time, this is the simplest project I've found and has a simple web UI: https://github.com/cocktailpeanut/dalai

It works for 7B/13B/30B/65B LLaMA and Alpaca (fine-tuned LLaMA which definitely works better). The smaller models at least should run on pretty much any computer.

I am not against easy mode options dude, for example I used to run GANs through command line. I replaced them with Upscayl when I found it. Convenience is king after all. Something about this one isn't right though. They are advertising it as a model they built meanwhile their own github show it to be a frontend of LLAMA. Why aren't they honest about it? Why use bots to spam about it? This causes me to not trust the executable they share to 1 to 1 compliation of the source code neither. I would still recommend looking for more decent alternatives. Btw, running it directly isn't that complicated

https://github.com/ggerganov/llama.cpp https://github.com/oobabooga/text-generation-webui https://github.com/mlc-ai/mlc-llm https://github.com/cocktailpeanut/dalai https://github.com/ido-pluto/catai (this is super easy to install but it doesnt provide an api or have integration with langchain)

This was easy to get running: https://github.com/cocktailpeanut/dalai with alpaca 13B (on my 16GB or ram)

I had it running before with Dalai (https://github.com/cocktailpeanut/dalai) but have since moved to using the browser based WebGPU method (https://mlc.ai/web-llm/) which uses Vicuna 7B and is quite good.

https://github.com/nsarrazin/serge let's you pick which model and runs in a container. For API https://github.com/cocktailpeanut/dalai looks super promising.

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.