SakanaAI
Sakana AI Joined Jul 2023 View on GitHub
- Stars
- 38,445
- across 61 public repos
- Rank
- #844
- of 94,827 organizations, top 0.9%
- Down 25 places this week
Repositories with 50+ stars
| Rank | Repository | Language | Stars |
|---|---|---|---|
| 3,455 | The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑🔬 | Jupyter Notebook | 14,978 |
| 8,130 | The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search | Python | 7,492 |
| 33,240 | Continuous Thought Machines, because thought takes time and reasoning is a process. | Python | 2,048 |
| 45,456 | ShinkaEvolve: Towards Open-Ended and Sample-Efficient Program Evolution 🧬 | Python | 1,506 |
| 47,587 | Official repository of Evolutionary Optimization of Model Merging Recipes | Python | 1,439 |
| 51,310 | Hypernetworks that adapt LLMs for specific benchmark tasks using only textual task description as the input | Python | 1,331 |
| 55,292 | A Self-adaptation Framework🐙 that adapts LLMs for unseen tasks in real-time! | Python | 1,227 |
| 64,162 | Shell | 1,040 | |
| 77,588 | Hypernetworks that update LLMs to remember factual information | Python | 843 |
| 95,252 | The Agentic Scientist: Orchestrating Coding Agents for Automated Scientific (Co-)Discovery | Python | 676 |
| 109,997 | A Tree Search Library with Flexible API for LLM Inference-Time Scaling | Python | 578 |
| 127,134 | Automating the Search for Artificial Life with Foundation Models! | Jupyter Notebook | 492 |
| 163,195 | Training teachers with reinforcement learning able to make LLMs learn how to reason for test time scaling. | Python | 371 |
| 166,813 | Code to train and evaluate Neural Attention Memory Models to obtain universally-applicable memory systems for transformers. | Python | 362 |
| 181,894 | Multi-Agent Self-Supervision | Python | 328 |
| 183,804 | DiffusionBlocks: Block-wise Neural Network Training via Diffusion Interpretation | Python | 324 |
| 191,001 | Python | 310 | |
| 220,021 | Cuda kernels for leveraging LLM sparsity to improve throughput and decrease the memory requirements during inference and training. | Cuda | 263 |
| 232,626 | PC-ALM | Python | 246 |
| 240,756 | The official repository of ALE-Bench | Python | 236 |
| 246,856 | Digital Red Queen: Adversarial Program Evolution in Core War with LLMs | Red | 229 |
| 250,491 | Extending the Context of Pretrained LLMs by Dropping Their Positional Embedding | Python | 225 |
| 315,986 | The code repository of the paper: Competition and Attraction Improve Model Fusion | Jupyter Notebook | 170 |
| 381,787 | Browser-based chat UI for TinySwallow-1.5B that runs without API calls. | CSS | 135 |
| 400,911 | Official implementation of "TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models" | Python | 127 |
| 400,911 | Generate publication-ready, editable draw.io figures for research papers from a methods section, using LLM agents. | TypeScript | 127 |
| 403,474 | Python | 126 | |
| 416,699 | Python | 121 | |
| 455,871 | Python | 108 | |
| 512,314 | Interactive multi-agent NCA ecosystem simulation | JavaScript | 93 |
| 550,054 | RePo: Language Models with Context Re-Positioning | Python | 85 |
| 600,866 | Jupyter Notebook | 76 | |
| 600,866 | Sheaf-ADMM | Python | 76 |
| 742,438 | Python | 58 | |
| 763,364 | Python-based chat demo for TinySwallow-1.5B that works completely offline | Python | 56 |
| 821,538 | Reimagining Agent-based Modeling with Large Language Model Agents via Shachi | Python | 51 |
Among 94,827 organizations
25k–40k stars: 673 organizations, including SakanaAI
Stars along the bottom, and organizations in each band on a log scale
Where the stars are
Languages
- Python 20.4k stars, 53% · 26 repos
- Jupyter Notebook 15.7k stars, 41% · 4 repos
- Shell 1k stars, 3% · 1 repo
- Cuda 263 stars, 1% · 1 repo
- Red 229 stars, 1% · 1 repo
- CSS 135 stars, <1% · 1 repo
- TypeScript 127 stars, <1% · 1 repo
- JavaScript 93 stars, <1% · 1 repo
When they were made
36 repos with 50+ stars, made between 2024 and 2026
Quick stats
- Next rank
- +5 stars to reach #843
- Next milestone
- +152,324 stars to reach the top 0.1%
- Public repos
- 61, 36 with 50+ stars
- Popular repos
- 8 over 1k stars, 1 over 10k stars
- Top repo
- AI-Scientist, #3,455 of all repos, 39% of stars
- Smaller repos
- 492 stars from repos under 50