No one knows about it! Which is ridiculous because batched requests with loras is mind blowing! Just like many other awesome backends like InternLM's backend, LiteLLM, Outline's VLLM fork, Aphroidte, exllamav2 batching servers and and such. Heck, a lot of trainers don't even publish the loras they merge into base models.
Personally we are waiting on the integration with constrained grammar before swapping to Lorax. Then I am going to add exl2 quantization support myself... I hope.
Also check out the new prefix caching, I see huge potential for batch processing purposes there!
Everything is moving so fast!
I will say that if you want to explore the forefront of this multi-LoRA inference, definitely worth giving LoRAX a look. We just added support for per-request model merging (https://predibase.github.io/lorax/guides/merging_adapters/) as an example, and are planning on continuing to double down on this idea of combining adapters in some pretty unique ways.
https://news.ycombinator.com/item?id=38505986
Zero interest for some reason.
Edit: Deepseek coder has 4 submissions to HN with almost zero interest.
I can't say I blame them either, there is a lot of insane crypto-like fraud in the LLM/GenAI space. I watch the space like a hawk... and I couldn't even tell you how to filter it, it's a combination of self-training from experience and just downloading and testing stuff myself.
I also hang out on a few Discord servers: - Nous Research - TogetherAI / Fireworks / Openrouter - LangChain - TheBloke AI - Mistral AI
These, along with a couple of newsletters, basically keep a pulse on things.
And yeah, /r/LocalLlama seems to be getting noisier.
TBH I just follow people and discuss stuff on huggingface directly now. Its not great, but at least its not discord.
Some are pretty good! Check out this little curated nugget: https://llm-tracker.info/
I used to follow one with a UI that resembled HN itself, but now I can't find it in my bookmarks, lol.
Discord is so time inefficient, its almost hilarious. For every incredible conversation between experts you observe, you have to weed through 200 times as much filler.
TBH I do not follow OpenAI much. I like my personal models local, and my workplace likes their models local as well.
We are getting a lot of great models out of China in particular (Yi, Qwen, InternLM, ChatGLM), and some good continuations like Solar.
Lots of amazing papers on architectures and long context are coming out.
Backends are going crazy. Outlines is shoving constrained generation everywhere, and Lorax is a LLM revelation as far as I'm concerned.
But you won't hear about any of this on Twitter/HN. Pretty much the only thing people tweet about is vllm/llama.cpp and llama/mistral, but there's a lot more out there than that.