📝Evaluating Pixel Language Models on Non-Standardized Languages 🔎We trained a German PIXEL model -- which performs strongly on dialect data 👥Alberto Muñoz-Ortiz, Verena Blaschke, @barbara_plank 🔗arxiv.org/abs/2412.09084 📁Main - Short

Happy to announce that I'm open-sourcing YugoGPT-base LLM - the best 7 billion parameter LLM for BCS (Serbian, Bosnian, and Croatian) languages! I hope that this contribution of mine will play its part in kicking off the local LLM ecosystem! You can find the model on HuggingFace: huggingface.co/gordicaleksa/… If you want to quickly get started with even more powerful models you can use RunaAI's API dev platform here: dev.runaai.com/ AI is the future and the latest paradigm shift in the arc of technological progress. Countries that fall behind in the AI race are putting their economies, national security, culture & language at risk. It's therefor of utmost importance that every country has a powerful regional LLM tailored to their language(s). The approach that big tech companies are taking is basically treating most of the world's languages as an afterthought - which is fine for them as it helps them reap some of the profits but not for companies and governments that actually use those languages in production ready systems. I want to build very powerful regional LLMs and this is just the first step. A big thank you to all of the project sponsors (listed in the README), and Nikola Ljubešić (@nljubesic), CLARINSI, and CLASSLA for help with BCS data!

ACL org announcement: 📢The list of accepted workshops in the ACL Conferences (@aclmeeting, @eaclmeeting, @naaclmeeting, @emnlpmeeting) in 2024 is out! Please help spread the word. Retweeting w/ references, esp. w/organisers information is very much appreciated - thanks! #NLProc

Adieu all! 🥹 #eacl2023