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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")

TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way.

TranslatedAll in one open-source whiteboard tool with mind, flowchart, freehand and etc. (SaaS)

  • collaboration
  • drawing
  • flowchart
  • localfirst

Powerline is a statusline plugin for vim, and provides statuslines and prompts for several other applications, including zsh, bash, tmux, IPython, Awesome and Qtile.

  • python
  • statusline
  • prompt
  • vim

Universal File Online Preview Project based on Spring-Boot

  • fileview
  • kkfileview
  • office-view
  • fileviewer

EF Core is a modern object-database mapper for .NET. It supports LINQ queries, change tracking, updates, and schema migrations.

  • entity-framework
  • database
  • c-sharp
  • dotnet-core

TranslatedIndustry-first professional AI Agent platform for controllable film & video production. From shorts to live-action with Hollywood-standard workflows. (The Chinese part states: the first industrial-grade, full-pipeline AI film and video production platform.)

RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.