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Source channel @githubtrending · Post #14909 · Jul 3

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#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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📰 Info_Dota2

@Info_Dota2 · Post #36386 · 01/28/2025, 12:00 AM

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Yuma “Yuma” Langlet, hard carry de HEROIC, habló sobre el desempeño de su equipo tras avanzar a los playoffs del campeonato FISSURE PLAYGROUND #1. ¿Esperabas este resultado? “La verdad, no. No deberíamos haber jugado este torneo en primer lugar, ya que ni siquiera participamos en las clasificatorias. Tampoco nos preparamos específicamente, así que llegamos sin muchas expectativas. Solo estamos tratando de mostrar nuestro mejor nivel de juego y ver qué podemos lograr con eso.” Si así lo lograron sin preparación, ¿qué hubiera sido con entrenamiento previo? 🔥 #ESB#Esports#Dota2#Heroic#Yuma @Info_Dota2

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