What is this?
Self-llm is a Chinese-language tutorial collection that teaches beginners how to configure environments, deploy, and fine-tune (full-parameter or LoRA) 50+ open-source large language models and multimodal models on Linux.
Self-llm is a Chinese-language tutorial collection that teaches beginners how to configure environments, deploy, and fine-tune (full-parameter or LoRA) 50+ open-source large language models and multimodal models on Linux.Is this a library I install, or a collection of tutorials?It is a collection of Jupyter Notebook tutorials and guides, one set per supported model, not a library, app, or framework you import.
It is a collection of Jupyter Notebook tutorials and guides, one set per supported model, not a library, app, or framework you import.Where should a beginner start?Start with environment setup, then move to model deployment, and finish with fine-tuning; beginners are advised to begin with easier models like Qwen1.5, InternLM2, or MiniCPM before browsing the full table of 50+ supported models.
Start with environment setup, then move to model deployment, and finish with fine-tuning; beginners are advised to begin with easier models like Qwen1.5, InternLM2, or MiniCPM before browsing the full table of 50+ supported models.Are all hardware platforms and models fully ready right now?Not all of them — the Muxi platform section is explicitly marked as not yet available, while Apple Silicon support is still being tested and expanded.
Not all of them — the Muxi platform section is explicitly marked as not yet available, while Apple Silicon support is still being tested and expanded.Who is this meant for?It targets Chinese students and self-learners who want to run and fine-tune open-source LLMs locally without API access, as a stepping stone before deeper LLM theory or application-development courses.
It targets Chinese students and self-learners who want to run and fine-tune open-source LLMs locally without API access, as a stepping stone before deeper LLM theory or application-development courses.What is Tianji (天机) mentioned as an example project?Tianji is one of the example mini-projects built with self-llm: a full-pipeline LLM application for social-etiquette scenarios, covering prompt engineering, agent building, data collection/fine-tuning, and RAG data cleaning.
Tianji is one of the example mini-projects built with self-llm: a full-pipeline LLM application for social-etiquette scenarios, covering prompt engineering, agent building, data collection/fine-tuning, and RAG data cleaning.Which deployment tools are covered in the tutorials?Depending on the model and hardware, guides show deployment via command-line calls, online demos, LangChain integration, and tools like vLLM, Ollama, LM Studio, llama.cpp, and sglang.
Depending on the model and hardware, guides show deployment via command-line calls, online demos, LangChain integration, and tools like vLLM, Ollama, LM Studio, llama.cpp, and sglang.Does it support non-Nvidia hardware?Yes, beyond the main Linux/GPU track there are dedicated sections for AMD GPUs (ROCm) and Huawei Ascend NPUs, with Apple Silicon support also in progress.
Yes, beyond the main Linux/GPU track there are dedicated sections for AMD GPUs (ROCm) and Huawei Ascend NPUs, with Apple Silicon support also in progress.Can I add a tutorial for a new model myself?Yes, the project explicitly invites contributors to open issues or submit pull requests to add tutorials for more models and hardware platforms.
Yes, the project explicitly invites contributors to open issues or submit pull requests to add tutorials for more models and hardware platforms.What are similar projects?verl, ms-swift, unsloth, vllm, ktransformers, halo, ollama, autumn-recruitment
verl, ms-swift, unsloth, vllm, ktransformers, halo, ollama, autumn-recruitment