Yağız Çalık (@weyaxi) 's Twitter Profile
Yağız Çalık

@weyaxi

Passionate about AI, Machine Learning, NLP, LLMs and Software Development | #opensource

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linkhttps://hf.co/Weyaxi calendar_today20-03-2020 09:33:59

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Yağız Çalık (@weyaxi) 's Twitter Profile Photo

Thrilled to announce our paper was accepted to AAAI-2026 PerFM! 🇸🇬✨ Can’t wait to be in Singapore for it. We also open-sourced our Human-Like-DPO dataset on Hugging Face 👇 10k+ samples designed to boost conversational naturalness in LLMs. Dataset: huggingface.co/datasets/Human…

Thrilled to announce our paper was accepted to AAAI-2026 PerFM! 🇸🇬✨
Can’t wait to be in Singapore for it.

We also open-sourced our Human-Like-DPO dataset on <a href="/huggingface/">Hugging Face</a> 👇
10k+ samples designed to boost conversational naturalness in LLMs.

Dataset: huggingface.co/datasets/Human…
Yağız Çalık (@weyaxi) 's Twitter Profile Photo

We just wrapped up Week 5 of Youth AI Initiative, and we officially left “text-only” AI behind. 🖼️🔊 This week was all about the frontier of Generative Media and Multimodal AI, taught by two people we know well: gokaygokay from fal and merve from Hugging Face 🚀 First up,

We just wrapped up Week 5 of <a href="/YouthAIInit/">Youth AI Initiative</a>, and we officially left “text-only” AI behind. 🖼️🔊

This week was all about the frontier of Generative Media and Multimodal AI, taught by two people we know well: <a href="/gokayfem/">gokaygokay</a> from <a href="/fal/">fal</a> and <a href="/mervenoyann/">merve</a> from <a href="/huggingface/">Hugging Face</a> 🚀

First up,
Liquid AI (@liquidai_) 's Twitter Profile Photo

Today we release LFM2.5-1.2B-Thinking, a reasoning model that runs entirely on-device. What needed a data center two years ago now runs on any phone with 900 MB of memory. > Trained specifically for concise reasoning > Generates internal thinking traces before producing answers

Today we release LFM2.5-1.2B-Thinking, a reasoning model that runs entirely on-device. What needed a data center two years ago now runs on any phone with 900 MB of memory.

&gt; Trained specifically for concise reasoning
&gt; Generates internal thinking traces before producing answers