1.jingyaogong / minimind
🧠 Train a 64M-parameter LLM from scratch in just 2h!
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13 repositories by Attention Score · Oct 28, 2026 – Nov 3, 2026 (UTC)
🧠 Train a 64M-parameter LLM from scratch in just 2h!
Bootstrap Kubernetes the hard way. No scripts.
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
A FREE comprehensive reverse engineering tutorial covering x86, x64, 32-bit/64-bit ARM, 8-bit AVR and 32-bit RISC-V architectures.
Examples and guides for using the Gemini API
TranslatedAirport recommendations, Clash / V2ray client configuration, and proxy tool guides
TranslatedThis project aims to share the technical principles of large models and practical experience (large model engineering, large model application deployment).
Bringing thousands of learners together to unpack DeepInfer through peer-reviewed explanations, documentation, and hands-on examples.
TranslatedJava backend knowledge graph🔥 Helping Java beginners grow
Translatedflink learning blog. http://www.54tianzhisheng.cn/ Covers Flink introduction, concepts, principles, hands-on practice, performance tuning, source code analysis, and more. Includes learning examples involving Flink Connector, Metrics, Library, DataStream API, Table API & SQL, and also shares large-scale project cases of Flink in production (PV/UV, log storage, real-time deduplication of 10 billion records, monitoring and alerting). You are welcome to support my column 《大数据实时计算引擎 Flink 实战与性能优化》 ("Big Data Real-Time Computing Engine Flink: Hands-On Practice and Performance Optimization")
Translated:books: This repository is a summary of the technical learning journey of the author, Xiao Fuge (小傅哥), from many years of working in front-line internet Java development. It aims to give everyone a clear and detailed learning tutorial, with a focus on writing about core Java content. If this repository helps you, please show your support (follow, like, share)!