[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-2270":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":14,"stars7d":17,"stars30d":18,"stars90d":16,"forks30d":16,"starsTrendScore":15,"compositeScore":19,"rankGlobal":10,"rankLanguage":10,"license":20,"archived":21,"fork":21,"defaultBranch":22,"hasWiki":21,"hasPages":23,"topics":24,"createdAt":10,"pushedAt":10,"updatedAt":27,"readmeContent":28,"aiSummary":29,"trendingCount":16,"starSnapshotCount":16,"syncStatus":30,"lastSyncTime":31,"discoverSource":32},2270,"neuroai","facebookresearch\u002Fneuroai","facebookresearch","Python suite for neuroscience research across all modalities.","https:\u002F\u002Ffacebookresearch.github.io\u002Fneuroai\u002F",null,"Python",243,56,6,18,0,13,77,5.27,"MIT License",false,"main",true,[25,26],"deep-learning","neuroscience","2026-06-12 02:00:39","\u003Ch1 align=\"center\">\n  \u003Cspan style=\"font-family: 'Segoe UI', 'Helvetica Neue', Arial, sans-serif; font-weight: 800; font-size: 3em; color: #4169e1; letter-spacing: -1px;\">Neuro AI\u003C\u002Fspan>\n\u003C\u002Fh1>\n\n\u003Cp align=\"center\">\n  \u003Cstrong style=\"font-size: 1.15em; letter-spacing: 0.04em;\">made easy\u003C\u002Fstrong>\n\u003C\u002Fp>\n\n\u003Cp align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Ffacebookresearch\u002Fneuroai\u002Factions\u002Fworkflows\u002Fci.yml\">\u003Cimg src=\"https:\u002F\u002Fgithub.com\u002Ffacebookresearch\u002Fneuroai\u002Factions\u002Fworkflows\u002Fci.yml\u002Fbadge.svg\" alt=\"CI\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Ffacebookresearch.github.io\u002Fneuroai\u002F\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fdocs-online-blue?logo=readthedocs&logoColor=white\" alt=\"Documentation\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Ffacebookresearch\u002Fneuroai\u002Fblob\u002Fmain\u002FLICENSE\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Flicense-MIT-green\" alt=\"License: MIT\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fwww.python.org\u002F\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fpython-3.12%2B-blue?logo=python&logoColor=white\" alt=\"Python 3.12+\">\u003C\u002Fa>\n\u003C\u002Fp>\n\n\n---\n\n\nSee the [full documentation](https:\u002F\u002Ffacebookresearch.github.io\u002Fneuroai\u002F) for interactive quickstarts, step-by-step tutorials, and the complete API reference.\n\n---\n\n## Packages\n\n### [NeuralSet](https:\u002F\u002Ffacebookresearch.github.io\u002Fneuroai\u002Fneuralset\u002Findex.html)\n\nBuild your efficient Neuro AI data loader.\n\n```bash\npip install neuralset\n```\n\n\n### [NeuralFetch](https:\u002F\u002Ffacebookresearch.github.io\u002Fneuroai\u002Fneuralfetch\u002Findex.html)\n\nFetch curated Neuro AI datasets.\n\n```bash\npip install neuralfetch\n```\n\n\n### [NeuralTrain](https:\u002F\u002Ffacebookresearch.github.io\u002Fneuroai\u002Fneuraltrain\u002Findex.html)\n\nTrain Neuro AI models at scale.\n\n```bash\npip install neuraltrain\n```\n\n\n### [NeuralBench](https:\u002F\u002Ffacebookresearch.github.io\u002Fneuroai\u002Fneuralbench\u002Findex.html)\n\nUnified benchmark for NeuroAI models.\n\n```bash\npip install neuralbench\n```\n\n---\n\n## Related projects\n\n- **[exca](https:\u002F\u002Ffacebookresearch.github.io\u002Fexca\u002F)** — Execution & caching framework powering neuroai's backbone\n\n---\n\n## License\n\nThis project is licensed under the [MIT License](LICENSE).\n\n\u003Csub>References to third-party content are subject to their own licenses.\u003C\u002Fsub>\n\n---\n\n## Citation\n\nIf you use `neuroai` in your research, please cite [NeuralSet: A High-Performing Python Package for Neuro-AI](https:\u002F\u002Fkingjr.github.io\u002Ffiles\u002Fneuralset.pdf):\n\n```bibtex\n@article{king2026neuralset,\n  title   = {NeuralSet: A High-Performing Python Package for Neuro-AI},\n  author  = {King, J-R. and Bel, C. and Evanson, L. and Gadonneix, J. and Houhamdi, S. and L{\\'e}vy, J. and Raugel, J. and Santos Revilla, A. and Zhang, M. and Bonnaire, J. and Caucheteux, C. and D{\\'e}fossez, A. and Desbordes, T. and Diego-Sim{\\'o}n, P. and Khanna, S. and Millet, J. and Orhan, P. and Panchavati, S. and Ratouchniak, A. and Thual, A. and Brooks, T. and Begany, K. and Benchetrit, Y. and Careil, M. and Banville, H. and d'Ascoli, S. and Dahan, S. and Rapin, J.},\n  year    = {2026},\n  url     = {https:\u002F\u002Fkingjr.github.io\u002Ffiles\u002Fneuralset.pdf},\n  note    = {Preprint; URL will be updated when the paper lands on arXiv}\n}\n```\n","Neuro AI 是一个用于多模态神经科学研究的Python套件。它包含了四个核心包：NeuralSet用于构建高效的数据加载器，NeuralFetch提供精选的数据集获取功能，NeuralTrain支持大规模模型训练，而NeuralBench则为神经AI模型提供统一的基准测试平台。这些工具利用深度学习技术来简化复杂的神经科学实验流程，并且易于安装使用。该项目适用于需要处理大量神经科学数据、进行模型训练及评估的研究场景。采用MIT许可证开放源代码，确保了广泛的可访问性和灵活性。",2,"2026-06-11 02:49:11","CREATED_QUERY"]