Supra2-IMG Demo
🖼
5
Tiny 100M text-to-image model demo (256x256)
🏗️ Building on HF
AxionLab
AxionLab-official
AI & ML interests
Owner of SupraLabs and iGPU Lover
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liked a Space about 16 hours ago
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SupraLabs/Supra2-IMG new activity about 18 hours ago
AxionLab-official/MiniBot-0.9M-Base:Card param count is ~9.5% low: 985,728 in the checkpoint vs ~900K on the cardOrganizations
liked a
Space about 16 hours ago
liked a
model about 16 hours ago
Card param count is ~9.5% low: 985,728 in the checkpoint vs ~900K on the card
1
#1 opened 1 day ago
by 
Compactbot
liked a
Space 2 days ago
Question
6
#1 opened 18 days ago
by 
GGUFGuy
liked a
Space 3 days ago
liked a
model 3 days ago
liked a
Space 3 days ago
Why do you want to join SupraLabs?
17
#1 opened 5 days ago
by 
LH-Tech-AI
liked a
model 4 days ago
liked a
Space 4 days ago
commented on BananaMind 2 Pro: We've (almost) matched SmolLM2 at 20x fewer tokens... Trained On a 5070 Ti 4 days ago
So I wrote it and told it to change only this part: And yes, it was trained on a 5070 TI
And didnt realize it changed everything else.Nice that you got that.
Bro just admit you use AI heavily
reacted to DavidAU's post with 😔 5 days ago
Post
8585
Qwen 3.5 9B - The Defiant, 27B power ; now with Qwen 3.8 Reasoning modes.
640 ARC-C for both 8bit and 4bit. Model exceeds 7 of 7 benchmarks for Qwen 3.5 9B, Qwen3.5 27B, Qwen3.6 35B-A3B, and meets Qwen 3.6 27B in some cases... and it does so in 4bit and 8bit. Regular and MTP (fast) NEO IMATRIX GGUFs provided. (this model is part of the Qwen 3.6 27B Fable Fusion 711 pipelines: 2200+ likes, 3 million + downloads)
NEW - Qwen 3.8 Reasoning Modes: 2 MTP quants (Q6/Q8) Now with 5 reasoning modes (2 new - Spoon / Einstein), and 5 instruct modes (2 new - Spoon / Einstein, all use ZERO REASONING TOKENS) all switchable on the fly via API, direct and "in chat" (yes - model control at the chat/message level). Model name has "plusIQ" in the name.
(there is also a extra robust "tools" version too.)
DavidAU/Qwen3.5-9B-The-Defiant-Fable-Uncensored-Heretic-NEO-IMATRIX-MAX-MTP-GGUF
PS: I have posted a 22k output example using "spoon" mode too.
640 ARC-C for both 8bit and 4bit. Model exceeds 7 of 7 benchmarks for Qwen 3.5 9B, Qwen3.5 27B, Qwen3.6 35B-A3B, and meets Qwen 3.6 27B in some cases... and it does so in 4bit and 8bit. Regular and MTP (fast) NEO IMATRIX GGUFs provided. (this model is part of the Qwen 3.6 27B Fable Fusion 711 pipelines: 2200+ likes, 3 million + downloads)
NEW - Qwen 3.8 Reasoning Modes: 2 MTP quants (Q6/Q8) Now with 5 reasoning modes (2 new - Spoon / Einstein), and 5 instruct modes (2 new - Spoon / Einstein, all use ZERO REASONING TOKENS) all switchable on the fly via API, direct and "in chat" (yes - model control at the chat/message level). Model name has "plusIQ" in the name.
(there is also a extra robust "tools" version too.)
DavidAU/Qwen3.5-9B-The-Defiant-Fable-Uncensored-Heretic-NEO-IMATRIX-MAX-MTP-GGUF
PS: I have posted a 22k output example using "spoon" mode too.
- 5 replies
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model 5 days ago
reacted to Datdanboi25's post with 🔥❤️ 7 days ago
Post
2959
100 likes on the Open SLM Leaderboard 🎉
176 models, 54 orgs, 5 benchmarks, and a whole community of support!
Thanks to everyone who’s contributed models, reported issues, suggested benchmark improvements, or used the leaderboard to compare and evaluate small language models.
It’s been awesome watching the leaderboard grow into a broader community resource for transparent and reproducible SLM evaluation.
Thank you all, and more to come 🚀
176 models, 54 orgs, 5 benchmarks, and a whole community of support!
Thanks to everyone who’s contributed models, reported issues, suggested benchmark improvements, or used the leaderboard to compare and evaluate small language models.
It’s been awesome watching the leaderboard grow into a broader community resource for transparent and reproducible SLM evaluation.
Thank you all, and more to come 🚀
- 1 reply
Could you please add my following models.
6
#142 opened 9 days ago
by 
DedeProGames
reacted to SeaWolf-AI's post with 🚀🔥 9 days ago
Post
5631
Instead of making the fly brain play games, we measured what it is for
Since the Drosophila connectome was released, people have had the fly brain doomscroll a feed, play Beat Saber, drive in GTA. Those demos show that the brain runs. We wanted to show what it is for.
So we gave it a looming object — one of the few things a fly brain is unambiguously built to detect — then deleted a single cell type and repeated the identical stimulus. Remove LC4, 126 cells out of 173,023, and the escape signal falls from 0.840 to 0.091. Eighty-nine percent of the danger signal is gone while the other 172,897 neurons run exactly as before.
Deleting neurons does not do this on its own, which is the whole point of the controls. LC11 is the same class and larger than LC4 — 143 cells and 9,940 outgoing connections against 126 and 7,846 — and removing every one of them changes the signal by 0.000000, to six decimal places. It has to be those 126.
No server and no GPU: a looming stimulus drives fewer than one percent of neurons above threshold, so the whole thing is 40 KB gzipped and runs in your browser.
Try deleting one yourself →
VIDraft/fruitfly-brain
The wiring is the measured connectome, but synaptic strength is a uniform count-based value and the dynamics are a firing-rate model of our choosing — a total-effect measurement of a model, not a recording from a fly. Male CNS connectome, FlyEM / HHMI Janelia with Google Research, Columbia and Harvard (2026), CC BY.
Since the Drosophila connectome was released, people have had the fly brain doomscroll a feed, play Beat Saber, drive in GTA. Those demos show that the brain runs. We wanted to show what it is for.
So we gave it a looming object — one of the few things a fly brain is unambiguously built to detect — then deleted a single cell type and repeated the identical stimulus. Remove LC4, 126 cells out of 173,023, and the escape signal falls from 0.840 to 0.091. Eighty-nine percent of the danger signal is gone while the other 172,897 neurons run exactly as before.
Deleting neurons does not do this on its own, which is the whole point of the controls. LC11 is the same class and larger than LC4 — 143 cells and 9,940 outgoing connections against 126 and 7,846 — and removing every one of them changes the signal by 0.000000, to six decimal places. It has to be those 126.
No server and no GPU: a looming stimulus drives fewer than one percent of neurons above threshold, so the whole thing is 40 KB gzipped and runs in your browser.
Try deleting one yourself →
VIDraft/fruitfly-brain
The wiring is the measured connectome, but synaptic strength is a uniform count-based value and the dynamics are a firing-rate model of our choosing — a total-effect measurement of a model, not a recording from a fly. Male CNS connectome, FlyEM / HHMI Janelia with Google Research, Columbia and Harvard (2026), CC BY.
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