🎆
ALL-ABOUT-LLM
  • 🥳Summary
  • 🐰TOTOTOlearn
    • ⚒️Evaluate
    • 🙇‍♂️Lossless Compression
      • 🧠Compressing for AGI
    • 👼Tutorials&Workshops
      • 🥰Introduction to Algorithms
        • 🐶The Role of Algorithms in Computing
      • 🧎‍♀️ACL 2023 Tutorial: Retrieval-based Language Models and Applications
      • 🐧Real_PEFT
    • 🧕Personality Traits&Bias in LLM
      • 👹Personality Traits in Large Language Models
    • 🔥openLLM
      • 🦅Aquila 悟道天鹰系列
      • 🌊百川大模型
    • 🌜AI Agents
      • 🍞Learning to Model the World with Language
      • 🪵ToolLLM
    • 👾MLLM
      • 🐐LLaVA: Large Language and Vision Assistant
    • 📃Surveys
    • 🙇‍♀️POSTS
      • 🔆拆解追溯 GPT-3.5 各项能力的起源
  • 🤖TOTOTODO
    • 🌚Challenges and Applications of Large Language Models
      • 😼Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback
      • 👏Challenges and Applications of Large Language Models
      • 🙆模型安全--A Watermark for Large Language Models
      • 🏸Inword： Bring games to life with AI NPCs
      • 💦Brain in a Vat: On Missing Pieces Towards Artificial General Intelligence in Large Language Models
    • 😃炼丹工具箱
      • 🌐Megatron-LM -nvidia
      • 🌸Colossal-AI: 让AI大模型更低成本、方便易用、高效扩展
      • 🙆‍♂️BMInf -- 一个用于PLM推理阶段的低资源工具包
      • 🦈LLaMA-Efficient-Tuning&text-generation-webui
      • 🪐Paramters and Definations
      • 🦙Chinese-Vicuna: A Chinese Instruction-following LLaMA-based Model —— 一个中文低资源的llama+lora方案
      • 🥳PEFT doc-cn
        • 🥳Quickstart
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  2. 炼丹工具箱

Megatron-LM -nvidia

Ongoing research training transformer models at scale

Previous炼丹工具箱NextColossal-AI: 让AI大模型更低成本、方便易用、高效扩展

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