Hey everyone, I’m looking for a way to use an open source local large language model (LLM) on Linux, particularly on low-spec hardware like Raspberry Pi, to generate lengthy, coherent stories of 10k+ words from a single prompt. I recall reading about methods described in scientific papers such as “Re3: Generating Longer Stories With Recursive Reprompting and Revision”, announced in this Twitter thread from October 2022 and “DOC: Improving Long Story Coherence With Detailed Outline Control”, announced in this Twitter thread from December 2022. These papers used GPT-3, and since it’s been a while since then, I was hoping there might be something similar made using only open source tools. Does anyone have experience with this or know of any resources that could help me achieve long, coherent story generation with an open source LLM? Any advice or pointers would be greatly appreciated. Thank you!
Have you tried GPT4All https://gpt4all.io/index.html ? It runs on CPU so is a bit slow, but it’s a way to run various LLM locally with an plug and play, easy to use solution. That said, LLM are huge, and perform better on GPU, provided you have a GPU big enough. Here is the trap. How much do you want to spend in a GPU ?
On GPU it is okay. GTX-1080 with a R5 3700X.
It has just written a 24 page tourist info booklet about the town I live in and a bunch of it is very inaccurate or outdated on the places to go. Fun and impressive anyway. Took only a few minutes.
If you get just the right gguf model (read the description when you download them to get the right K-optimization or whatever it’s called) and actually use multithreading (llamacpp supports multithreading so in theory gpt4all should too), then it’s reasonably fast. I’ve achieved roughly half the speed of ChatGPT just on an 8 core amd fx with ddr3 ram. Even 20b models can be usably fast.