anseryuer/Local_LLM_Deployment_Guide_Chinese
本地部署大语言模型的中文教学
This guide teaches individuals how to run large language models (LLMs) on their personal computer without relying on paid API services. It takes users from understanding LLM basics and hardware requirements to practical deployment methods, enabling them to chat with models locally or build custom AI tools. This resource is for anyone who wants to leverage LLMs privately and cost-effectively.
Use this if you want to run powerful AI language models directly on your computer to save money on API calls, experiment with AI, or develop personalized tools like translators or summarizers.
Not ideal if you are looking for an actively maintained, frequently updated guide, as the author states it will no longer be updated.
Stars
43
Forks
4
Language
—
License
MIT
Category
Last pushed
Mar 05, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/anseryuer/Local_LLM_Deployment_Guide_Chinese"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Goekdeniz-Guelmez/mlx-lm-lora
Train Large Language Models on MLX.
uber-research/PPLM
Plug and Play Language Model implementation. Allows to steer topic and attributes of GPT-2 models.
VHellendoorn/Code-LMs
Guide to using pre-trained large language models of source code
ssbuild/chatglm_finetuning
chatglm 6b finetuning and alpaca finetuning
jarobyte91/pytorch_beam_search
A lightweight implementation of Beam Search for sequence models in PyTorch.