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Mex Ivanov

MexIvanov
evilfreelancer's profile picture 21world's profile picture skatzR's profile picture
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AI & ML interests

NLP, Coding, Quantum Computing and more.

Recent Activity

reacted to fffiloni's post with 🤗 about 9 hours ago
✨ PASD Magnify is back on Hugging Face Spaces https://huggingface.co/spaces/fffiloni/PASD PASD isn’t recent, but still delivers strong results — worth restoring rather than replacing. Getting it to run again wasn’t a simple dependency issue. It relied on parts of diffusers that no longer exist, while moving to Gradio 6 forced a much newer HF stack — and I couldn’t modify the original source directly. Recreating the old environment wasn’t practical. So I patched the downloaded code at runtime before import and made it compatible with today’s stack. That ended up being the only approach that held without forking or freezing everything to outdated versions. If you’ve used it before (or are curious), feel free to give it another try.
liked a dataset about 1 month ago
Crownelius/Opus-4.6-Reasoning-3300x
reacted to marksverdhei's post with 👍 2 months ago
Poll: Will 2026 be the year of subquadratic attention? The transformer architecture is cursed by its computational complexity. It is why you run out of tokens and have to compact. But some would argue that this is a feature not a bug and that this is also why these models are so good. We've been doing a lot of research on trying to make equally good models that are computationally cheaper, But so far, none of the approaches have stood the test of time. Or so it seems. Please vote, don't be shy. Remember that the Dunning-Kruger effect is very real, so the person who knows less about transformers than you is going to vote. We want everyone's opinion, no matter confidence. 👍 if you think at least one frontier model* will have no O(n^2) attention by the end of 2026 🔥 If you disagree * Frontier models - models that match / outperform the flagship claude, gemini or chatgpt at the time on multiple popular benchmarks
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