dalai VS serge

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.

Very cool, this looks like a combination of chatbot-ui and llama-cpp-python? A similar project I've been using is https://github.com/serge-chat/serge. Nous-Hermes-Llama2-13b is my daily driver and scores high on coding evaluations (https://huggingface.co/spaces/mike-ravkine/can-ai-code-resul...).

You might be pleased to hear that nothing really stops you from doing this today. If you ran Serge[0] on a Mac with Tailscale, you could hack together a decently-accelerated Llama chatbot.

[0] https://github.com/serge-chat/serge

Cannot help you with libraries specifically but both Serge and ChatUI are built using SvelteKit, so the code might be of some use to you.

Serge made it really easy for me to get started, but it all CPU-based.

All that said this project probably solves your problem: https://github.com/serge-chat/serge

You can play a little bit with more straightforward local models (the simplest to setup is https://github.com/nsarrazin/serge ), to see that any LLM is basically a party trick.