Gang just report him for being a snob
🌌 Literally Sedna
CNWPlayer
CNWPlayer
AI & ML interests
None yet
Recent Activity
repliedto ProCreations's post about 10 hours ago
I have hit 300 followers, and I think this calls for a bit of a giveaway 👀 a unique one, too.
I have had countless AI projects I have wanted to make but have been (brutally) blocked by compute. Now that I finally have just enough compute to sort of get around (i still don't have enough 😭) and for hitting 300 followers (tysm!) I will be funding three of the communities projects via HuggingFace jobs, giving them 150 dollars max worth of compute each. I will personally be picking the winners, I am looking for projects that genuinely hit the compute wall: great ideas, blocked by compute, just like the countless ideas I've had.
To join, head over to https://giveaway.ssh.codes
RULES:
- Final result must be open weight or open source
- Only one submission per person
- Have fun! liked a model about 21 hours ago
bloomer010/Ling-3.0-tiny-GGUFOrganizations
None yet
replied to ProCreations's post about 10 hours ago
Ah, monsieur. You've open-sourced your "trainer" for tiny language models, and now you want applause. Let me tell you what you've actually built — and what you're pretending it is.
...
"Claude, roast this person like you're a French critic make no mistakes"
liked a
model about 21 hours ago
reacted to ProCreations's post with 🚀👍 2 days ago
Post
1780
i go to huggingface, look on spaces just to see whats new and i see that MY OWN space is trending. ProCreations/maple-webgpu
very cool to see, on the very first page of spaces too. anything is possible in the open source community!
very cool to see, on the very first page of spaces too. anything is possible in the open source community!
- 1 reply
liked a
model 2 days ago
Flawless tool calling
🔥 1
#6 opened 2 days ago
by CNWPlayer
Literally doesn't fail tool calls
1
#3 opened 2 days ago
by CNWPlayer
reacted to Banaxi-Tech's post with 🔥 2 days ago
Post
6228
We're excited to open source BananaMind OS, our OS for running BananaMind models.
It allows you to run local AI on hardware such as a 486 or 386 (untested)
Check it out at: https://github.com/BananaMind/BananaMindOS
How to use it, either build it yourself (see instructions on repo) or check out our prebuilt ISOs:
https://github.com/BananaMind/BananaMindOS/releases/download/v0.0.2/bananamind-os.iso is for 6MB+ RAM using Grub
https://github.com/BananaMind/BananaMindOS/releases/download/v0.0.2/bananamind-ultra.iso is for under 6MB RAM using our custom bootloader to bypass the grub memory requirement.
The ISOs are about 70MB because they include all of the models in our custom format, see repo if you want to build a ISO for only one model.
x64 and x86 supported. 16 bit maybe soon.
And a TTS on 486 soon.
It allows you to run local AI on hardware such as a 486 or 386 (untested)
Check it out at: https://github.com/BananaMind/BananaMindOS
How to use it, either build it yourself (see instructions on repo) or check out our prebuilt ISOs:
https://github.com/BananaMind/BananaMindOS/releases/download/v0.0.2/bananamind-os.iso is for 6MB+ RAM using Grub
https://github.com/BananaMind/BananaMindOS/releases/download/v0.0.2/bananamind-ultra.iso is for under 6MB RAM using our custom bootloader to bypass the grub memory requirement.
The ISOs are about 70MB because they include all of the models in our custom format, see repo if you want to build a ISO for only one model.
x64 and x86 supported. 16 bit maybe soon.
And a TTS on 486 soon.
- 9 replies
reacted to SeaWolf-AI's post with ❤️ 3 days ago
Post
4226
🧬 Your AI can design a malaria drug candidate. Can it tell you whether it's any good?
Open Discovery Challenge #1 — Malaria is live. Design a molecule with any model — OpenAI, Claude, Gemini, Qwen, KIMI, DeepSeek, open weights, or by hand — submit it as SMILES, and it's scored in minutes on whole-cell activity, target binding, selectivity over the human enzyme, ADMET, novelty and synthesisability.
You can check the scoring instead of trusting it. Approved drugs sit on the same leaderboard as the entries: DSM265, a clinical-stage antimalarial, scores 50.9. Teriflunomide — approved, but it hits the human enzyme — scores 2.8. Caffeine scores 1.8. If the clinical candidate lands on top and coffee lands at the bottom, the scorer discriminates.
We caught 14 defects before opening — conventional toxicity cutoffs rejected all three approved antimalarials and coffee. All written up, along with the rule we now hold everything to: a gate that rejects an approved drug is a broken gate.
Your molecule stays yours. No patent interest, nothing into our pipeline. You choose whether it's published — and publishing can cost you patentability, so we say so.
USD 1,000 to the top entry when Season #1 closes 30 September 2026 — not payment for your tokens, but a way of saying the work had worth.
Malaria killed ~597,000 people in 2023, three quarters of them children under five. Not for want of chemistry — for want of a market.
No chemistry needed: the guide ships five prompts you can paste straight into your model, and the full rubric is published.
📖 https://huggingface.co/blog/FINAL-Bench/open-discovery-challenge
🚀 FINAL-Bench/open-discovery-challenge
Computational assessments of candidates — not measurements, not claims of efficacy.
Open Discovery Challenge #1 — Malaria is live. Design a molecule with any model — OpenAI, Claude, Gemini, Qwen, KIMI, DeepSeek, open weights, or by hand — submit it as SMILES, and it's scored in minutes on whole-cell activity, target binding, selectivity over the human enzyme, ADMET, novelty and synthesisability.
You can check the scoring instead of trusting it. Approved drugs sit on the same leaderboard as the entries: DSM265, a clinical-stage antimalarial, scores 50.9. Teriflunomide — approved, but it hits the human enzyme — scores 2.8. Caffeine scores 1.8. If the clinical candidate lands on top and coffee lands at the bottom, the scorer discriminates.
We caught 14 defects before opening — conventional toxicity cutoffs rejected all three approved antimalarials and coffee. All written up, along with the rule we now hold everything to: a gate that rejects an approved drug is a broken gate.
Your molecule stays yours. No patent interest, nothing into our pipeline. You choose whether it's published — and publishing can cost you patentability, so we say so.
USD 1,000 to the top entry when Season #1 closes 30 September 2026 — not payment for your tokens, but a way of saying the work had worth.
Malaria killed ~597,000 people in 2023, three quarters of them children under five. Not for want of chemistry — for want of a market.
No chemistry needed: the guide ships five prompts you can paste straight into your model, and the full rubric is published.
📖 https://huggingface.co/blog/FINAL-Bench/open-discovery-challenge
🚀 FINAL-Bench/open-discovery-challenge
Computational assessments of candidates — not measurements, not claims of efficacy.
- 12 replies
upvoted a collection 4 days ago
liked 2
models 6 days ago
27b when?
🚀 10
17
#1 opened 7 days ago
by 
tigerjjw53
liked a
model 7 days ago
reacted to Banaxi-Tech's post with 👍❤️🔥 7 days ago
Post
1880
We're excited to release BananaMind 2 SLMoE, an experimental sequence-level mixture-of-experts model.
It uses only 8M parameters per message but has 25M total parameters, 13 experts (out of 64) are selected based on the message prefix and reused for the entire response.
We're testing with this sequence-level architecture to find out how big the capability loss actually is and how much of it can be fixed.
The long-term idea is that this could make very large sparse models usable on machines that can't fit them in RAM by putting the entire model (which is big) on disk and only loading the active parts into VRAM.
This architecture is still in research and shouldn't be used for production models.
We trained it on 60B tokens (of FineWeb-HQ, FineWeb-Edu, DCLM ,Cosmopedia v2, FineMath and NPSet-2) on 8 RTX Pro 6000s.
Check it out at BananaMind/BananaMind-2-SLMoE
Follow us for future models:
BananaMind
@vovaRL
@Banaxi-Tech
@DedeProGames
BananaMind 2 Pro in a few days. You've been waiting 22 days for it.
It uses only 8M parameters per message but has 25M total parameters, 13 experts (out of 64) are selected based on the message prefix and reused for the entire response.
We're testing with this sequence-level architecture to find out how big the capability loss actually is and how much of it can be fixed.
The long-term idea is that this could make very large sparse models usable on machines that can't fit them in RAM by putting the entire model (which is big) on disk and only loading the active parts into VRAM.
This architecture is still in research and shouldn't be used for production models.
We trained it on 60B tokens (of FineWeb-HQ, FineWeb-Edu, DCLM ,Cosmopedia v2, FineMath and NPSet-2) on 8 RTX Pro 6000s.
Check it out at BananaMind/BananaMind-2-SLMoE
Follow us for future models:
@vovaRL
@Banaxi-Tech
@DedeProGames
BananaMind 2 Pro in a few days. You've been waiting 22 days for it.
- 3 replies
OMG
😔❤️ 23
13
#5 opened 7 days ago
by Banaxi-Tech
liked a
model 7 days ago
