Hi there, If I'm looking to use LLM AI in a similar way like Stable Diffusion, i.e. running it on my own PC using pre-trained models (checkpoints?) - where would I start?

If I would want to have access to it on my mobile devices - is this a possibility?

If I would then later want to create workflows using these AI tools - say use the LLM to generate prompts and automatically run them on Stable Diffusion - is this a possibility?

I'm consistently frustrated with ChatGPT seemingly not beeing able to remember a chat history past a certain point. Would a self-run model be better in that regard (i.e. will I be able to reference somethin in a chat thread that happened 2 weeks ago?)

Are there tools that would allow cross-thread referencing?

I have no expert knowledge whatsoever, but I don't shy away from spending hours learning new staff. Will I be able to take steps working towards my own personal AI assistant? Or would this be way out of scope for a hobbyist?

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[–] dtjones@lemmy.world 3 points 1 year ago (3 children)

Depends on your hardware and how far you're willing to go. For serious development I think you need at least 12-16 GB of VRAM, but there's still some things you can do with ~8. If you just have a cpu, you can still test some models but generation will be slow.

I'd recommend trying out the oogabooga webui. This should work with quite a few models on hugging face. Hopefully I don't get in trouble for recommending a subreddit but r/localllama has a lot of other great resources and us a very active community. They're doing exactly what you want.

As far as your other questions...

Accessing it on your phone is going to be tricky. You would most likely want to host it somewhere but I'm not sure how easy that is for someone without a bit of software background. Maybe there is a good service for this, huggingface might offer something.
Cross thread referencing is an interesting idea. I think you would need to create a log store of all your conversations and then embed those into a a vector store (like milvus or weaviate or qdrant). This is a little tricky since you have to decide how to chunk your conversations, but it is doable. The next step is somewhat open ended. You could always query your vector store with any questions that you are already sending your model, and then pass any hits to the model along with your original question. Alternatively, you could tell the model to check for other conversations and trigger a function call to do this on command. A good starting point might be this example, which makes references to a hardware manual in a Q&A style chatbot.
Using an LLM with stable diffusion: not especially sure what you are hoping to get out of this. Maybe to reduce boilerplate prompt writing? But yes you can finetune a model to handle this and then have the model execute a function that calls stable diffusion and returns the results. I am pretty sure langchain provides a framework for this. Langchain is almost certainly a tool you will want to become familiar with.

[–] Solvena@lemmy.world 1 points 1 year ago (1 children)

Thanks for the input!

I recently built a new PC to handle Stable Diffusion, that gives me 12GB of VRAM to work with. I also started to self-host a few things on a VPS recently, so I have a bit of a basis there.

As for Stable Diffusion integration: I do storytelling/worldbuilding as a hobby and find LLM's to be an amazing tool to "brainstorm with myself". It would be amazing if I could tell the LLM to "make a picture of the new character" and it would connect to and prompt SD accordingly. I assume that this is out of scope of what's currently possible, but something like that would be my goal. I will certainly have a look at langchain as you proposed. Also that's the context of me asking about cross referencing and context length. I've been working with ChatGPT, and while it is an amazing tool it had me bummed out when it couldn't reference a character that was developed a couple hours earlier (even in the same thread). The cross referencing solution that you sketched above might work for me, but I guess it'll take a while to learn how to do it.

Given this as a bit of context: where should I start? Downloading Llama 2 as another reply suggests and go from there?

[–] dtjones@lemmy.world 1 points 1 year ago

Seems reasonable. I'll add in that there are models specifically finetuned for storytelling. You might check out this thread for some other model suggestions. I think you will also likely want to find a framework for RLHF.

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