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Source channel @githubtrending · Post #15539 · Mar 5

#python#agent#llm#llm_agent#llm_reasoning#machine_learning_systems#mlsys#reinforcement_learning#rl AReaL is a free, open-source system for fast asynchronous reinforcement learning to train large AI models in math, coding, search, and agents. It decouples generation and training for up to 2.77x speedup, stable performance, and easy setup on single or 1000+ GPUs with algorithms like GRPO/PPO. Install via git/pip, run examples like GSM8K math instantly. You benefit by building top AI agents affordably and quickly, reproducing results with shared data/models, saving time/money vs. slow synchronous tools. https://github.com/inclusionAI/AReaL

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djangoproject

@djangoproject · Post #132 · 09/01/2016, 02:47 PM

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https://bit.ly/coroutines At Open Source Bridge and #PyGotham in 2015, and at SCALE14x, I demonstrated that you can code a Python 3 #async framework in under an hour. I start the demo by writing a callback-based async framework, built on non-blocking sockets and a simple event loop. Then I adapt the framework to use generator-based #coroutines, which are cleaner than callbacks but still more efficient than threads for async I/O.

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#pygotham #async #coroutines