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!
You can try setting up Ollama on your RPi, then use a highly-quantized variant of the Mistral model (or quantize it yourself with GGUF+llama.cpp). You can do some very heavy quantization (2-bit), which will increase the error rate. But if you are only planning to use the generated text as a starting point, it might be useful nevertheless. Also see: https://github.com/ollama/ollama/blob/main/docs/import.md#importing-pytorch--safetensors
Here are some pre-quantized variants of Mistral 7B: https://huggingface.co/TheBloke/Mistral-7B-v0.1-GGUF
(all the tools and models I have mentioned in my comment are free and open-source, and beyond that, require no uplink during operation)