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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",[],[211,369,370,371,372,373,374,226,375,227,376,377,378,379,380,381,382,383,229,230,296],"rl","miles rl training","miles","FP8","Enterprise","SGLang","learning","router","ready","alignment","slime","megatron","Megatron-LM","throughput","production-ready",{"skillNo":385,"name":364,"nameZh":13,"description":365,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":13,"repositoryNo":205,"starsCount":206,"licenseSpdxId":207,"licenseFileUrl":13,"sourceHtmlUrl":386,"categories":387,"keywords":388,"publishedAt":231},"01M6KQK36YJNBJ379SE7T9GBN6","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FAI-Training\u002Fmiles\u002FSKILL.md",[],[211,369,370,371,372,373,374,226,375,227,376,377,378,379,380,381,382,383,229,230,296],{"skillNo":390,"name":391,"nameZh":13,"description":392,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":13,"repositoryNo":205,"starsCount":206,"licenseSpdxId":207,"licenseFileUrl":13,"sourceHtmlUrl":393,"categories":394,"keywords":395,"publishedAt":231},"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",[],[341,211,380,396,216,397,283,398,377,284,399,314,400,401,402,403,291,404,383,405,296],"training llms megatron","pipeline","context","efficiency","apex","H100","Megatron-Core","Model Parallelism","advanced","sequence",{"skillNo":407,"name":391,"nameZh":13,"description":392,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":13,"repositoryNo":205,"starsCount":206,"licenseSpdxId":207,"licenseFileUrl":13,"sourceHtmlUrl":408,"categories":409,"keywords":410,"publishedAt":231},"01M6KQJRM8H767ZSZD0CHWK87Y","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FAI-Training\u002Fmegatron-core\u002FSKILL.md",[],[341,211,380,396,216,397,283,398,377,284,399,314,400,401,402,403,291,404,383,405,296],{"skillNo":412,"name":413,"nameZh":13,"description":414,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":13,"repositoryNo":205,"starsCount":206,"licenseSpdxId":207,"licenseFileUrl":13,"sourceHtmlUrl":415,"categories":416,"keywords":418,"publishedAt":231},"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",[417],{"categoryNo":5,"categoryName":8,"taxonomyType":6,"taxonomyTypeDesc":7},[419,420,421,341,422,423,424,425,426,427,428,284,429,430,287,431,432,433,229,230],"Llama","factory","LLaMA Factory","research","support","code","Fine-Tuning","LoRA","QLoRA","HuggingFace","webui","bit","8-Bit","No-Code","with",{"skillNo":435,"name":413,"nameZh":13,"description":414,"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":231},"01M6KQJF9X5E6JGNN82MD9X95H","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FAI-Training\u002Fllama-factory\u002FSKILL.md",[438],{"categoryNo":5,"categoryName":8,"taxonomyType":6,"taxonomyTypeDesc":7},[419,420,421,341,422,423,424,425,426,427,428,284,429,430,287,431,432,433,229,230],{"skillNo":441,"name":442,"nameZh":13,"description":443,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":13,"repositoryNo":205,"starsCount":206,"licenseSpdxId":207,"licenseFileUrl":13,"sourceHtmlUrl":444,"categories":445,"keywords":446,"publishedAt":231},"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",[],[341,447,448,295,215,425,426,226,345,449,283,227,450,451,286,452,453,454,455,229,456,296],"LitGPT","implementing llms litgpt","phi","single-file","clean","Model Architecture","Lightning AI","LLM Implementation","layers","single",{"skillNo":458,"name":442,"nameZh":13,"description":443,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":13,"repositoryNo":205,"starsCount":206,"licenseSpdxId":207,"licenseFileUrl":13,"sourceHtmlUrl":459,"categories":460,"keywords":461,"publishedAt":231},"01M6KQHX4TAYGQWVNRYSE6WK0X","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FAI-Training\u002Flitgpt\u002FSKILL.md",[],[341,447,448,295,215,425,426,226,345,449,283,227,450,451,286,452,453,454,455,229,456,296],10874,18]