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Use when training large MoE models with FP8\u002FINT4, needing train-inference alignment, or requiring speculative RL for maximum throughput.","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FAI-Training\u002Fmiles\u002Fmiles\u002FSKILL.md",[],[240,390,391,392,393,394,395,220,396,255,397,398,399,400,401,402,403,404,228,229,231],"rl","miles rl training","miles","FP8","Enterprise","SGLang","learning","router","ready","alignment","slime","megatron","Megatron-LM","throughput","production-ready",{"skillNo":406,"name":385,"nameZh":13,"description":386,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":13,"repositoryNo":205,"starsCount":206,"licenseSpdxId":207,"licenseFileUrl":13,"sourceHtmlUrl":407,"categories":408,"keywords":409,"publishedAt":232},"01M6KQK36YJNBJ379SE7T9GBN6","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FAI-Training\u002Fmiles\u002FSKILL.md",[],[240,390,391,392,393,394,395,220,396,255,397,398,399,400,401,402,403,404,228,229,231],{"skillNo":411,"name":412,"nameZh":13,"description":413,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":13,"repositoryNo":205,"starsCount":206,"licenseSpdxId":207,"licenseFileUrl":13,"sourceHtmlUrl":414,"categories":415,"keywords":416,"publishedAt":232},"01M6KQJXY9HPMWRB7PXBEF29BC","training-llms-megatron","Trains large language models (2B-462B parameters) using NVIDIA Megatron-Core with advanced parallelism strategies. Use when training models >1B parameters, need maximum GPU efficiency (47% MFU on H100), or require tensor\u002Fpipeline\u002Fsequence\u002Fcontext\u002Fexpert parallelism. Production-ready framework used for Nemotron, LLaMA, DeepSeek.","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FAI-Training\u002Fmegatron-core\u002Fmegatron-core\u002FSKILL.md",[],[215,240,401,417,245,418,307,419,398,308,420,337,421,422,423,424,315,425,404,426,231],"training llms megatron","pipeline","context","efficiency","apex","H100","Megatron-Core","Model Parallelism","advanced","sequence",{"skillNo":428,"name":412,"nameZh":13,"description":413,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":13,"repositoryNo":205,"starsCount":206,"licenseSpdxId":207,"licenseFileUrl":13,"sourceHtmlUrl":429,"categories":430,"keywords":431,"publishedAt":232},"01M6KQJRM8H767ZSZD0CHWK87Y","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FAI-Training\u002Fmegatron-core\u002FSKILL.md",[],[215,240,401,417,245,418,307,419,398,308,420,337,421,422,423,424,315,425,404,426,231],{"skillNo":433,"name":434,"nameZh":13,"description":435,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":13,"repositoryNo":205,"starsCount":206,"licenseSpdxId":207,"licenseFileUrl":13,"sourceHtmlUrl":436,"categories":437,"keywords":439,"publishedAt":232},"01M6KQJMDQ974E2Q475NCSVJNF","llama-factory","Expert guidance for fine-tuning LLMs with LLaMA-Factory - WebUI no-code, 100+ models, 2\u002F3\u002F4\u002F5\u002F6\u002F8-bit QLoRA, multimodal support","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FAI-Training\u002Fllama-factory\u002Fllama-factory\u002FSKILL.md",[438],{"categoryNo":5,"categoryName":8,"taxonomyType":6,"taxonomyTypeDesc":7},[440,441,442,215,443,444,445,446,447,448,449,308,450,451,311,452,453,454,228,229],"Llama","factory","LLaMA Factory","research","support","code","Fine-Tuning","LoRA","QLoRA","HuggingFace","webui","bit","8-Bit","No-Code","with",{"skillNo":456,"name":434,"nameZh":13,"description":435,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":13,"repositoryNo":205,"starsCount":206,"licenseSpdxId":207,"licenseFileUrl":13,"sourceHtmlUrl":457,"categories":458,"keywords":460,"publishedAt":232},"01M6KQJF9X5E6JGNN82MD9X95H","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FAI-Training\u002Fllama-factory\u002FSKILL.md",[459],{"categoryNo":5,"categoryName":8,"taxonomyType":6,"taxonomyTypeDesc":7},[440,441,442,215,443,444,445,446,447,448,449,308,450,451,311,452,453,454,228,229],{"skillNo":462,"name":463,"nameZh":13,"description":464,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":13,"repositoryNo":205,"starsCount":206,"licenseSpdxId":207,"licenseFileUrl":13,"sourceHtmlUrl":465,"categories":466,"keywords":467,"publishedAt":232},"01M6KQJ22RQ1A2X74MZRZV6SFS","implementing-llms-litgpt","Implements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistral). Use when need clean model implementations, educational understanding of architectures, or production fine-tuning with LoRA\u002FQLoRA. Single-file implementations, no abstraction layers.","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FAI-Training\u002Flitgpt\u002Flitgpt\u002FSKILL.md",[],[215,468,469,319,244,446,447,220,211,470,307,255,471,472,310,473,474,475,476,228,477,231],"LitGPT","implementing llms litgpt","phi","single-file","clean","Model Architecture","Lightning AI","LLM Implementation","layers","single",10891,18]