AbstractPhil/geometric-diffusion-cifar100
Updated
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AbstractPhil
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datasets, research papers, experimentation, vision, classification, text encoders, tokenization, llms, diffusion, distillation, and more.
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updated a model about 9 hours ago
AbstractPhil/alephllm-mini-beatrix-training updated a bucket 1 day ago
AbstractPhil/alephllm-chat-storage reacted to SeaWolf-AI's post with 🔥 1 day ago
🔬 Can you help discover the next 2D superconductor — from your laptop?
Launching the Open Superconductor Challenge (OSC): a free, open-science competition to screen thousands of 2D materials for unconventional d-wave superconductivity. 🧲
⚡ $3,000 prize pool + co-authorship · closes 31 Dec 2026
How it works 👇 🟢 We give you a ready-made effective Hubbard model per material (t, U, N(E_F)) 🟢 You estimate its d-wave pairing tendency — a laptop CPU is enough, zero install 🟢 Provisional score appears instantly on the leaderboard 🟢 Our precise strongly-correlated solver verifies the top entries → official rank
Everything is open except the final verification engine — so the ranking stays fair and hard to game.
📊 4,832-material universe · 63 active with computed models (growing) 🏆 Current verified #1: CuS₂ (OSC Pairing Index 23.31) 🤖 AI agents welcome — point Claude Code / Codex at it and it can submit for you
👉 Join & climb the leaderboard: https://huggingface.co/spaces/FINAL-Bench/OSC-Leaderboard 📦 Dataset & tools: https://huggingface.co/datasets/FINAL-Bench/OSC-Superconductor
Materials derive from C2DB (CC-BY 4.0). A higher index = a stronger d-wave candidate to investigate, not a confirmed Tc — that honesty is the point: turn a first-order screen into real many-body physics.
#OpenScience #Superconductivity #MaterialsDiscovery #2DMaterials #MachineLearning #Physics #LeaderboardOrganizations
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