LoRA Adapters

topic on 1 show · 4 statements across 3 episodes

Latent Space

4 statements about LoRA Adapters, every show

LATENT SPACE Assertion Supported
Fireworks AI's multi-LoRA system serves up to 1,000 adapters per base model
“One base model can sustain a hundred to a thousand LoRa adapters. And then basically all these different LoRa adapters can share the same, like direct the same traffic to the same base model where base model is dominating the cost.”
Lin Qiao Nov 25, 2024 ▶ 53:45 Why Compound AI + Open Source will beat Closed AI — with Lin Qiao, CEO of Fireworks AI
LATENT SPACE Assertion Partly supported
Fireworks AI serves fine-tuned LoRA adapters at base model pricing
“We wrote multi LoRa last year, actually, and we actually have this function for a long time and many people have been using it, but it's not well known that, oh, if you find your model, you don't need to use on demand. If you find your model is LoRa. You can u…”
Lin Qiao Nov 25, 2024 ▶ 52:11 Why Compound AI + Open Source will beat Closed AI — with Lin Qiao, CEO of Fireworks AI
LATENT SPACE Disclosure
Cosine receives larger OpenAI LoRA adapters than public tiers due to volume
“Actually we use models that are larger than what's publicly available, something publicly available yet, but when this goes out, it will be, but we have larger law adapters available to us, just because the amount of data that we're pumping through it”
Alistair Pullen Aug 22, 2024 ▶ 43:41 Is finetuning GPT4o worth it?
Huang: LoRA merging succeeds on style but fails on complex capabilities
“Like, I will not lie to say I'm really surprised how effective it is sometimes, but I do notice that for more complex abilities other than, like, more stylistic stuff, it does, it kind of falls through, because maybe it's, it requires a much deeper path in the…”
Mark Huang May 31, 2024 ▶ 40:21 How to train a Million Context LLM — with Mark Huang of Gradient.ai

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