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Source channel @githubtrending · Post #14845 · Jun 20

#jupyter_notebook#ai#artificial_intelligence#chatgpt#deep_learning#from_scratch#gpt#language_model#large_language_models#llm#machine_learning#python#pytorch#transformer You can learn how to build your own large language model (LLM) like GPT from scratch with clear, step-by-step guidance, including coding, training, and fine-tuning, all explained with examples and diagrams. This approach mirrors how big models like ChatGPT are made but is designed to run on a regular laptop without special hardware. You also get access to code for loading pretrained models and fine-tuning them for tasks like text classification or instruction following. This helps you deeply understand how LLMs work inside and lets you create your own functional AI assistant, gaining practical skills in AI development[1][2][3][4]. https://github.com/rasbt/LLMs-from-scratch

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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 #