alkinun's picture

alkinun

AtAndDev

·

AI & ML interests

LLMs, Alignment, Merging, Unsloth, DPO, SFT, ORPO, SPIN..

Recent Activity

reacted to openfree's post with ❤️ about 20 hours ago

# 🧬 Protein Genesis AI: Design Proteins with Just a Prompt ## 🤔 Current Challenges in Protein Design Traditional protein design faces critical barriers: - 💰 High costs ($1M - $10M+) & long development cycles (2-3 years) - 🔬 Complex equipment and expert knowledge required - 📉 Low success rates (<10%) - ⏰ Time-consuming experimental validation ## ✨ Our Solution: Protein Genesis AI Transform protein design through simple natural language input: ``` "Design a protein that targets cancer cells" "Create an enzyme that breaks down plastic" ``` ### Key Features - 🤖 AI-powered automated design - 📊 Real-time analysis & optimization - 🔬 Instant 3D visualization - 💾 Immediate PDB file generation ## 🎯 Applications ### Medical & Industrial - 🏥 Drug development - 💉 Antibody design - 🏭 Industrial enzymes - ♻️ Environmental solutions ### Research & Education - 🔬 Basic research - 📚 Educational tools - 🧫 Experimental design - 📈 Data analysis ## 💫 Key Advantages - 👨‍💻 No coding or technical expertise needed - ⚡ Results in minutes (vs. years) - 💰 90% cost reduction - 🌐 Accessible anywhere ## 🎓 Who Needs This? - 🏢 Biotech companies - 🏥 Pharmaceutical research - 🎓 Academic institutions - 🧪 Research laboratories ## 🌟 Why It Matters Protein Genesis AI democratizes protein design by transforming complex processes into simple text prompts. This breakthrough accelerates scientific discovery, potentially leading to faster drug development and innovative biotechnology solutions. The future of protein design starts with a simple prompt! 🚀 https://huggingface.co/spaces/openfree/ProteinGenesis

reacted to openfree's post with 🤗 about 20 hours ago

# 🧬 Protein Genesis AI: Design Proteins with Just a Prompt ## 🤔 Current Challenges in Protein Design Traditional protein design faces critical barriers: - 💰 High costs ($1M - $10M+) & long development cycles (2-3 years) - 🔬 Complex equipment and expert knowledge required - 📉 Low success rates (<10%) - ⏰ Time-consuming experimental validation ## ✨ Our Solution: Protein Genesis AI Transform protein design through simple natural language input: ``` "Design a protein that targets cancer cells" "Create an enzyme that breaks down plastic" ``` ### Key Features - 🤖 AI-powered automated design - 📊 Real-time analysis & optimization - 🔬 Instant 3D visualization - 💾 Immediate PDB file generation ## 🎯 Applications ### Medical & Industrial - 🏥 Drug development - 💉 Antibody design - 🏭 Industrial enzymes - ♻️ Environmental solutions ### Research & Education - 🔬 Basic research - 📚 Educational tools - 🧫 Experimental design - 📈 Data analysis ## 💫 Key Advantages - 👨‍💻 No coding or technical expertise needed - ⚡ Results in minutes (vs. years) - 💰 90% cost reduction - 🌐 Accessible anywhere ## 🎓 Who Needs This? - 🏢 Biotech companies - 🏥 Pharmaceutical research - 🎓 Academic institutions - 🧪 Research laboratories ## 🌟 Why It Matters Protein Genesis AI democratizes protein design by transforming complex processes into simple text prompts. This breakthrough accelerates scientific discovery, potentially leading to faster drug development and innovative biotechnology solutions. The future of protein design starts with a simple prompt! 🚀 https://huggingface.co/spaces/openfree/ProteinGenesis

reacted to openfree's post with 👀 about 20 hours ago

# 🧬 Protein Genesis AI: Design Proteins with Just a Prompt ## 🤔 Current Challenges in Protein Design Traditional protein design faces critical barriers: - 💰 High costs ($1M - $10M+) & long development cycles (2-3 years) - 🔬 Complex equipment and expert knowledge required - 📉 Low success rates (<10%) - ⏰ Time-consuming experimental validation ## ✨ Our Solution: Protein Genesis AI Transform protein design through simple natural language input: ``` "Design a protein that targets cancer cells" "Create an enzyme that breaks down plastic" ``` ### Key Features - 🤖 AI-powered automated design - 📊 Real-time analysis & optimization - 🔬 Instant 3D visualization - 💾 Immediate PDB file generation ## 🎯 Applications ### Medical & Industrial - 🏥 Drug development - 💉 Antibody design - 🏭 Industrial enzymes - ♻️ Environmental solutions ### Research & Education - 🔬 Basic research - 📚 Educational tools - 🧫 Experimental design - 📈 Data analysis ## 💫 Key Advantages - 👨‍💻 No coding or technical expertise needed - ⚡ Results in minutes (vs. years) - 💰 90% cost reduction - 🌐 Accessible anywhere ## 🎓 Who Needs This? - 🏢 Biotech companies - 🏥 Pharmaceutical research - 🎓 Academic institutions - 🧪 Research laboratories ## 🌟 Why It Matters Protein Genesis AI democratizes protein design by transforming complex processes into simple text prompts. This breakthrough accelerates scientific discovery, potentially leading to faster drug development and innovative biotechnology solutions. The future of protein design starts with a simple prompt! 🚀 https://huggingface.co/spaces/openfree/ProteinGenesis

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AtAndDev's activity

upvoted a paper 1 day ago

2 OLMo 2 Furious

Paper • 2501.00656 • Published 5 days ago • 12

upvoted a paper 4 days ago

1.58-bit FLUX

Paper • 2412.18653 • Published 12 days ago • 66

upvoted a paper 16 days ago

Instruction Pre-Training: Language Models are Supervised Multitask Learners

Paper • 2406.14491 • Published Jun 20, 2024 • 86

upvoted a paper 22 days ago

Phi-4 Technical Report

Paper • 2412.08905 • Published 25 days ago • 96

upvoted a paper 23 days ago

The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Paper • 2406.17557 • Published Jun 25, 2024 • 88

upvoted a paper 25 days ago

KTO: Model Alignment as Prospect Theoretic Optimization

Paper • 2402.01306 • Published Feb 2, 2024 • 16

upvoted a collection 28 days ago

NuminaMath

Datasets and models for training SOTA math LLMs. See our GitHub for training & inference code: https://github.com/project-numina/aimo-progress-prize • 6 items • Updated Jul 21, 2024 • 69

upvoted 2 papers about 1 month ago

Large Language Models Can Self-Improve in Long-context Reasoning

Paper • 2411.08147 • Published Nov 12, 2024 • 63

O1 Replication Journey -- Part 2: Surpassing O1-preview through Simple Distillation, Big Progress or Bitter Lesson?

Paper • 2411.16489 • Published Nov 25, 2024 • 41

upvoted 2 collections about 1 month ago

🧠 Reasoning Models

7 items • Updated 6 days ago • 36

QwQ

Qwen with Questions • 2 items • Updated Nov 28, 2024 • 54

upvoted 4 papers about 1 month ago

Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking

Paper • 2403.09629 • Published Mar 14, 2024 • 75

V-STaR: Training Verifiers for Self-Taught Reasoners

Paper • 2402.06457 • Published Feb 9, 2024 • 9

Let's Verify Step by Step

Paper • 2305.20050 • Published May 31, 2023 • 10

Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning

Paper • 2406.12050 • Published Jun 17, 2024 • 19

upvoted a collection about 2 months ago

Top LLM

Collection of TOP Open Source LLM, Sort by Best on top • 6 items • Updated Jul 26, 2024 • 13

upvoted a paper about 2 months ago

Large Language Models Orchestrating Structured Reasoning Achieve Kaggle Grandmaster Level

Paper • 2411.03562 • Published Nov 5, 2024 • 64

upvoted 3 papers 2 months ago

What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective

Paper • 2410.23743 • Published Oct 31, 2024 • 59

LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations

Paper • 2410.02707 • Published Oct 3, 2024 • 48

GPT-4o System Card

Paper • 2410.21276 • Published Oct 25, 2024 • 82