Adarsh Zolekar
adarshzolekar
AI & ML interests
Passionate about AI & ML, Deep Learning and related AI domains. Exploring models, datasets and applications while contributing to the Hugging Face community.
Recent Activity
upvoted
a
paper
5 days ago
mHC: Manifold-Constrained Hyper-Connections
reacted
to
mike-ravkine's
post
with ❤️
5 days ago
Happy 2026 everyone!
I've been busy working on some new ranking/position methodologies and excited to start sharing some results.
Plot legends:
- X = truncation rate (low = good)
- ? = confusion rate (low = good)
- blue bars = average completion tokens (low = good)
- black diamonds = CI-banded performance (high = good)
- cluster squares = models inside this group are equivalent
https://huggingface.co/openai/gpt-oss-120b remains the king in all dimensions of interest: truncation rates, completion lengths and performance. If I had but one complaint it's the reason_effort does not seem to actually work - more on this soon.
Second is a 3-way tie in performance between the Qwen3-235B-2507 we all know and love with an unexpected entrant - https://huggingface.co/ByteDance-Seed/Seed-OSS-36B-Instruct
This is a very capable model and it's reasoning effort controls actually works, but you should absolutely not leave it on the default "unlimited" - enable a sensible limit (4k works well for 8k context length).
Third place is another 3-way tie, this one between Seed-OSS-36B (it straddles the CI boundary between 2nd and 3rd place), https://huggingface.co/Qwen/Qwen3-Next-80B-A3B-Instruct (demonstrating that full attention may be overrated after all and gated is the way to go) and the newly released https://huggingface.co/zai-org/GLM-4.7 which offers excellent across the board performance with some of the shortest reasoning traces I've seen so far.
reacted
to
unmodeled-tyler's
post
with 👍
5 days ago
Happy New Year, Hugging Face!
It's been a crazy year for me! This year I launched VANTA Research as a solo operator and managed to push out 14 original open source finetunes and 5 datasets in the span of about 4 months, completely on my own.
The reception has been much higher than I ever anticipated and sincerely appreciate everyone that's checked out my work thus far.
The good news is, I'm just getting started! In 2026 you can expect even more original models from VANTA Research, more open source datasets, and maybe some other cool things as well? 👀
2026 is gonna be big for AI in general, and I can't wait to experience it with all of you!
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