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Source channel @githubtrending · Post #14909 · Jul 3

#other#agent#llm#rag Happy-LLM is a free, open-source learning project that helps you deeply understand large language models (LLMs) from basics to advanced training and applications. It teaches you key concepts like NLP, Transformer architecture, pretraining, and how to build and train your own LLaMA2 model step-by-step. You also learn practical skills like fine-tuning and using cutting-edge techniques such as Retrieval-Augmented Generation (RAG) and intelligent agents. This project is ideal if you know some Python and deep learning, and it offers both theory and hands-on code to help you master LLM development and apply it in real-world AI tasks. This can boost your skills and confidence in AI model building and research. https://github.com/datawhalechina/happy-llm

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RCNN Ticker

@RCNNticker · Post #315 · 12/19/2017, 04:21 PM

全球第五个单人六重蓝竹笋 也是 呆瓜 @DuangWB (原 @DuangW) 的第二个单六 于 12 月 10 日 清晨 06:49 (中国 04:49) 耗时 5h18min 再次在澳大利亚布里斯班完成 距第四个单六竹笋被呆瓜于 11 月 26 日 耗时 8h48min 完成 仅过两周 #Homogeneous

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В журнале Electrochemical Materials and Technologies вышла обзорная работа "H/D exchange studies of methane activation mechanisms in heterogeneous catalysis" 🔗https://doi.org/10.15826/elmattech.2023.2.014 🔗https://journals.urfu.ru/index.php/elmattech/article/view/6883 В данном обзоре подробно рассматривается механизм конверсии метана и анализируются существующие теоретические и экспериментальные подходы к изотопному обмену H/D между метаном и каталитическими системами: #CH4#methane#conversion#isotope#catalyst#bonds#homogeneous#exchange #