3 ms·
Even if it doesn't initially, the fact that it's being released so permissively is massive - stable diffusion was made far more powerful by being hackable at al
by pksebben 4y ago
Even if it doesn't initially, the fact that it's being released so permissively is massive - stable diffusion was made far more powerful by being hackable at all levels and I can't imagine we won't see the same here.
I imagine things like control nets that restrict output to parsable types, LoRa style adaptations that allow mixable "attitudes", that sort of thing.
Very different underlying architecture from diffusers, ofc. But the action of open source is the same - a million monkeys with a million xterms and so forth.
- edkennedy 4y agoI'm really hoping for the ability to load in different sets of trained material as embeddings/textual inversions like in Stable Diffusion. Imagine scanning in some of your favorite philosophy and design books and throwing them with small weighting as a little flavor to your answer. The crossovers between LLM and Stable Diffusion type models (like Loras) is such a fascinating space to explore.
- alex_sf 4y agoThis already exists for LLaMA, I'm sure it'll be implemented for StableLM as well. https://github.com/lxe/simple-llm-finetuner https://github.com/lxe/simple-llm-finetuner
- pksebben 4y agogood looks on the link! I was experimenting with script writing the other day and thought "gee, I really wish I could finetune on Beckett plays specifically". I don't know if anyone else has experienced this same tipping point, but when I used to have ideas, I would look them up and discover that implementing them was probably out of scope. These days, I think "wouldn't it be cool..." and immediately stumble on a way to make it happen, by accident.
- cheald 4y agoThis has been around for GPT models for a while in the form of "soft prompts", which are rather approximate to textual inversion in the Stable Diffusion space.