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Source channel @githubtrending · Post #14815 · Jun 10

#jupyter_notebook#chatglm#chatglm3#gemma_2b_it#glm_4#internlm2#llama3#llm#lora#minicpm#q_wen#qwen#qwen1_5#qwen2 This guide helps beginners set up and use open-source large language models (LLMs) on Linux or cloud platforms like AutoDL, with step-by-step instructions for environment setup, model deployment, and fine-tuning for models such as LLaMA, ChatGLM, and InternLM[2][4][5]. It covers everything from basic installation to advanced techniques like LoRA and distributed fine-tuning, and supports integration with tools like LangChain and online demo deployment. The main benefit is making powerful AI models accessible and easy to use for students, researchers, and anyone interested in experimenting with or customizing LLMs for their own projects[2][4][5]. https://github.com/datawhalechina/self-llm

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@githubtrending · Post #15595 · 04/01/2026, 11:30 AM

#go#distribution_spec#helm#kubernetes#oci#oci_distribution#opencontainers#zot Zot is a lightweight, production-ready OCI-native container registry for storing images, Helm charts, SBOMs, and other artifacts without vendor lock-in. It offers built-in authentication (OIDC, LDAP), storage options (S3, Azure), scanning, caching to cut Docker Hub limits/latency, and ARM/edge support as a single binary. You benefit by easily self-hosting a secure, scalable alternative to Docker Hub, saving costs, boosting speed, and enabling secret-less workflows on any device. https://github.com/project-zot/zot