ExLlama is an extremely optimized GPTQ backend for LLaMA models. It features much lower VRAM usage and much higher speeds due to not relying on unoptimized transformers code.

It is highly optimized model loader for GPTQ models. It's an alternative to options like AutoGPTQ or GPTQ-for-LLaMA, and provides faster text generation speeds.

With this update, anyone running GGML exclusively might find some interesting results switching over to a quantized model and testing the changes. I haven't had a chance yet myself, but I will post some of my own benchmarks and results if I find the time for it.

I for one am excited to see the efficiency battles begin. Getting compute down is going to be the most important hurdles to overcome.

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[–] Blaed 2 points 1 year ago* (last edited 1 year ago)

I'm with you there. I love how Mosaic just fed the entire Great Gatsby to StoryWriter. This is the sort of context length I need in my life. Would make my projects so much easier. I don't think we're too far from having it on consumer hardware.

You should check out my latest post - which ironically addresses parts of your first comment, but you still need a lot of VRAM... 6000+ tokens context is now possible with ExLlama.

It's crazy to see how fast these developments are happening!