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Source channel @githubtrending · Post #14835 · Jun 17
#jupyter_notebook#jax Flax is a library for creating neural networks with JAX. It offers a flexible way to build and analyze these networks. The new Flax NNX API makes it easier to work with neural networks by using regular Python objects, which helps in creating, debugging, and analyzing models more efficiently. This means users can express their models in a more intuitive way, making it simpler to develop and modify neural networks. Flax also provides many tools and examples to help users get started quickly. https://github.com/google/flax
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@R4marketing · Post #806 · 08/13/2021, 08:00 AM
Совсем лайтовая статья для новичков "10 главных конструкций языка R". Содержание: - Комментарии - Переменные и векторы - Внешние модули - Ввод и вывод - Присваивание и сравнение - Условный оператор if - Цикл for - Функции - Классы, методы и объекты #статьи #easy
@testflightynoti · Post #37780 · 05/07/2026, 08:30 PM
#Futubull#Easy#Investment Join the Futubull-Easy Investment beta on ✈️#TestFlight 🔗 Link: https://testflight.apple.com/join/LXJdcvBn Shared by Dimitri
@WangZhuanZhan · Post #34299 · 10/23/2024, 12:23 PM
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@wangzhuanzhan · Post #33280 · 09/23/2024, 06:10 AM
F-f绯f闻w计j划h- 绯闻计划 Easy A (2010) 直达链接：https://pan.quark.cn/s/1b65684910c6 #绯闻计划#Easy A #破处女王#现代红字 链接：https://link3.cc/sf_com #电影#喜剧#美国#10年代
@WangZhuanZhan · Post #34066 · 10/15/2024, 05:50 AM
T-t通t天t大d盗d- 通天大盗 通天大盜 (1987) 直达链接：https://pan.quark.cn/s/c40ba0abe557 #通天大盗#通天大盜 #妙婿向钱冲#Easy Money 链接：https://link3.cc/sf_com #电影#喜剧#香港#80年代
@wangzhuanzhan · Post #32222 · 09/03/2024, 08:49 AM
S-s水s性x杨y花h- 水性杨花 Easy Virtue (1928) 直达链接：https://pan.quark.cn/s/49ce72903d4a #水性杨花#Easy Virtue #放浪#轻浮的德行 链接：https://link3.cc/sf_com #电影#喜剧#美国#50年代之前
@testflightynoti · Post #37748 · 05/07/2026, 08:21 AM
#Easy#Credit#T#i#ch#nh#s Join the Easy Credit - Tài chính số beta on ✈️#TestFlight 🔗 Link: https://testflight.apple.com/join/B8XYxOWV Shared by Dimitri
@githubtrending · Post #15433 · 01/23/2026, 02:30 PM
#python#deepseek#demo#easy#embedding#flask#gpt#huggingface_transformers#llm#mcp#multimodal#openai#qwen#rag#sentence_transformers#ui#vllm#vlm UltraRAG is a lightweight framework that makes building retrieval-augmented generation (RAG) systems simple and fast. It uses a low-code approach where you write just dozens of lines of YAML configuration instead of complex code to create sophisticated AI workflows with conditional logic and loops. The framework includes a visual development environment where you can drag-and-drop to build pipelines, adjust parameters in real-time, and instantly convert your logic into interactive chat applications. This means you can deploy powerful AI systems that ground answers in your own data—reducing hallucinations and improving accuracy—without needing extensive coding expertise or lengthy development cycles. https://github.com/OpenBMB/UltraRAG