kandinskylab/KVAE-3D-2.0-t4s16
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Artem
kabachuha
AI & ML interests
deep learning, natural language processing, text2image, text2video, computer vision, fusion power
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kabachuha/Qwen3-4B-Instruct-2507-SOMbliteratedOrganizations
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LoRA-Camera-Control
3
#15 opened 23 days ago
by 
HK-wang
Eval request: p-e-w / gpt-oss-20b-heretic-ara-v3
β€οΈ 5
2
#583 opened 25 days ago
by kabachuha
βThe doom lies in yourself, not in your name.β
π 7
403
#15 opened 7 months ago
by 
jukofyork
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UGI Eval?
1
#1 opened 26 days ago
by kabachuha
Any ETA for the updates?
3
#52 opened 29 days ago
by kabachuha
reactedto MaziyarPanahi's post with π₯ 26 days ago
Post
4738
DNA, mRNA, proteins, AI. I spent the last year going deep into computational biology as an ML engineer. This is Part I of what I found. π§¬
In 2024, AlphaFold won the Nobel Prize in Chemistry.
By 2026, the open-source community had built alternatives that outperform it.
That's the story I find most interesting about protein AI right now. Not just the science (which is incredible), but the speed at which open-source caught up. Multiple teams, independently, reproduced and then exceeded AlphaFold 3's accuracy with permissive licenses. The field went from prediction to generation: we're not just modeling known proteins anymore, we're designing new ones.
I spent months mapping this landscape for ML engineers. What the architectures actually are (spoiler: transformers and diffusion models), which tools to use for what, and which ones you can actually ship commercially.
New post on the Hugging Face blog: https://huggingface.co/blog/MaziyarPanahi/protein-ai-landscape
Hope you all enjoy! π€
In 2024, AlphaFold won the Nobel Prize in Chemistry.
By 2026, the open-source community had built alternatives that outperform it.
That's the story I find most interesting about protein AI right now. Not just the science (which is incredible), but the speed at which open-source caught up. Multiple teams, independently, reproduced and then exceeded AlphaFold 3's accuracy with permissive licenses. The field went from prediction to generation: we're not just modeling known proteins anymore, we're designing new ones.
I spent months mapping this landscape for ML engineers. What the architectures actually are (spoiler: transformers and diffusion models), which tools to use for what, and which ones you can actually ship commercially.
New post on the Hugging Face blog: https://huggingface.co/blog/MaziyarPanahi/protein-ai-landscape
Hope you all enjoy! π€
- 2 replies
Does it work with multimodal?
1
#1 opened 26 days ago
by 
BingoBird
liked 2
models 27 days ago
RIP
π€ 10
2
#44 opened 27 days ago
by kabachuha
liked 2
models 28 days ago
