The "memory usage" section of the README highlights the surprising fact that image generation models need much less memory than text-based language models. ChatGPT itself is by far the most resource-hungry part of the system.
Why is that so? It seems counterintuitive. A single picture snapped with a phone takes more space to store than the text of all the books in a typical home library, yet Stable Diffusion runs with 5 GB of RAM while LLAMA needs 130 GB.
Why is that so? It seems counterintuitive. A single picture snapped with a phone takes more space to store than the text of all the books in a typical home library, yet Stable Diffusion runs with 5 GB of RAM while LLAMA needs 130 GB.
Can someone illuminate what's going on here?