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Translated"开源大模型食用指南" (Open-Source Large Model Usage Guide): a tutorial tailor-made for Chinese users on quickly fine-tuning (full-parameter/LoRA) and deploying domestic and international open-source large language models (LLM) and multimodal large models (MLLM) in a Linux environment

Translated🌊Deeply integrates top global academic, financial, and educational resources: the academic section gathers papers from authoritative platforms such as JSTOR, Taylor & Francis, and Cambridge University Press, and connects to the vast e-book collection of the Z-Library shadow library; the education section includes textbooks from Hong Kong and Singapore, from primary school through high school, as well as university subject textbooks; the financial section aggregates in-depth research reports from top institutions such as Citron (香橼), Morgan, and Nomura, all in order to break down information silos and build an inclusive knowledge base that provides equal access to knowledge.

  • academic
  • economics
  • humanities
  • research

FLUX, Stable Diffusion, SDXL, SD3, LoRA, Fine Tuning, DreamBooth, Training, Automatic1111, Forge WebUI, SwarmUI, DeepFake, TTS, Animation, Text To Video, Tutorials, Guides, Lectures, Courses, ComfyUI, Google Colab, RunPod, Kaggle, NoteBooks, ControlNet, TTS, Voice Cloning, AI, AI News, ML, ML News, News, Tech, Tech News, Kohya, Midjourney, RunPod

We unified the interfaces of instruction-tuning data (e.g., CoT data), multiple LLMs and parameter-efficient methods (e.g., lora, p-tuning) together for easy use. We welcome open-source enthusiasts to initiate any meaningful PR on this repo and integrate as many LLM related technologies as possible. 我们打造了方便研究人员上手和使用大模型等微调平台,我们欢迎开源爱好者发起任何有意义的pr!