[DreamGen]

Why I use Llama:

- Ability to self host. This unlocks few things: (1) Customized serving stack with various logit processors, etc. (2) More cost efficient inference.

- Ability to fine tune. Most stock instruct models are quite lame at AI story-writing and role-play and produce slop.

There aren't really any pain points specific to Llama, but if we are creating a wish list:

- Keep the pre-training data diverse. There is a worrying trend where some companies apply heavy handed filtering on the pre-training data that's not just based on quality, but also on content. Quality based filtering is understandable and desirable, but please, keep the pre-training dataset diverse :)

- Efficient inference. Open source is way behind closed source here. TensorRT-LLM is probably the most efficient from what's out there, but it's mostly closed source. Maybe Meta could contribute to some of the open source projects like vLLM (or maybe something lower level...).

- A lot of the improvements we saw recently came from post-training, post-SFT improvements. And it's not just the datasets (which clearly you can't just release), but also algorithms -- and most labs are quite secretive about the details here. The open-source community relies on DPO a lot (and more recently, KTO), since it's easy, but empirically it's not that great.