We changed the way we handle multimodal inputs in Outlines. Most libraries will give the prompt a special role, separate it from the other inputs. We don’t anymore.

📝 I have been meaning to write this for a while now, but after reading @remilouf.bsky.social's post on the potential of structured generation for LLMs and a post on SerDes debt deriving from Pydantic usage, I decided I should not wait any longer. So here is my new blog post:

🦀 Do you like Rust? 🇫🇷 Do you like Paris? Then you'll love the conference, Rust In Paris, that my colleague Yvan Sraka is delivering his talk, Beyond Procedural Macros: A Trait-Based Framework for Bindgen, at next month! www.rustinparis.com

This was absolutely my favorite talk from today! Love it / scared of it

Outlines 0.1.9 release is out! Small release, but some highlights: - First contribution by @chicham! - You can now use enums in outlines.generate.choice - Compilation time improvements. - Using the rust-native JSON-schema to regex, rather than the Python implementation

This is actually good to show skeptics of structured generation @dottxtai.bsky.social. Demonstrates very clearly that you can stop the model from fighting the constraints by telling it how it’s constrained, even if those constraints might seem absurd (like only using words from the King James Bible)

HF has done, and keeps doing, a lot of good in the AI ecosystem. I’ll die on this hill.

More insults under an apology post on Bluesky than under any outrageous post on Twitter. Be the change you want to see in the world or something like that.

Check out our new YouTube video. We're trying out kind of an interview format, so let me know if you love/hate this

Looking at the comments of this one, I think this is actually the Bad Place

The comments on this are unnecessarily hateful. I thought this place was better.

Give @dottxtai.bsky.social a follow for quality structured generation content!

A new paper, "Let Me Speak Freely" has been spreading rumors that structured generation hurts LLM evaluation performance. Well, we've taken a look and found serious issue in this paper, and shown, once again, that structured generation *improves* evaluation performance!

The "Let Me Speak Freely" got way too much traction too easily, despite a few serious issues. Well aware of Brandolini's law we published a thorough rebuttal of the main conclusion, highlighted the key methodological flaws and taught a few things in the process. Hope you enjoy it!

Our new blog post is out! @willkurt.bsky.social provides a rebuttal for a reasonably well known paper which concluded that structured generation with LLMs always resulted in worse performance. We do not find the same thing. blog.dottxt.co/say-what-you...

Y'ALL this is my first @dottxtai.bsky.social video to break 1k views!!!!! youtu.be/_SK2sO0_DEY?...

What’s the best LLM observability tool today?

👋 New followers I’m Rémi, co-founder and CEO of @dottxtai.bsky.social. We do structured generation with LLM, which means we are able to enforce constraints on the output (regex, JSON Schema, Grammar) during inference time. It’s very cool. dottxt.co

I wake up every day with 100 new followers now. The Starter Packs were a brilliant idea ✨

Hello Bluesky! We're here now. Wonderful to be in the Good Place. We'll be posting demos, interesting tidbits, and boosting cool AI stuff on here. dottxt.co

(Reposting from X) I did a tiny side project: a program that automatically generates a properly formatted .ics file from a text description (e.g. copy/paste an email) using an LLM, and imports it to your favorite calendar app! Structured generation is cool -- shoutout @remilouf.bsky.social and .txt

📊 One weird trick to parse earnings reports! Wall Street analysts HATE this! Use LLMs to convert messy SEC filings into clean CSV data using structured generation. The one weird trick? Convert your HTML to markdown + use Outlines. Link below 👇

To celebrate the release of @huggingface.bsky.social’s new SmolLM2 series of models we created a fun demo: the Bunny B1. The Bunny B1 shows how a small device using a SmolLM2 model + Outlines can consistently map natural language requests to the correct app! Check it out in this gif!

Week-end read

Outlines is a great library for structured generation for LLMs/VLMs, which is really helpful for many use cases. @remilouf.bsky.social and the team are working towards a 1.0.0 release with an API that looks very nice, in my opinion.

Phan et al, found a method to mitigate some of the tokenization problems Karpathy mentioned by projecting tokens into byte space. The key to their method is to develop a map between statistically equivalent token and byte-level models.

Ok what did I miss