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Source channel @githubtrending · Post #14926 · Jul 8

#jupyter_notebook#artificial_intelligence#book#large_language_models#llm#llms#oreilly#oreilly_books You can learn how to use Large Language Models (LLMs) effectively through the book *Hands-On Large Language Models* by Jay Alammar and Maarten Grootendorst. This book uses nearly 300 custom illustrations to explain key concepts and practical tools for working with LLMs, including tokenization, transformers, prompt engineering, fine-tuning, and advanced text generation. It also provides runnable code examples in Google Colab, making it easy to practice and apply what you learn. This resource helps you understand and build your own LLM applications confidently, saving you time and effort in mastering complex AI technology. It’s highly recommended for anyone wanting hands-on experience with LLMs. https://github.com/HandsOnLLM/Hands-On-Large-Language-Models

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Crypto M - Crypto News

@CryptoM · Post #65294 · 04/12/2026, 03:15 PM

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🚀 TRON Network Implements Proposal 106 to Enhance Compatibility TRON Network has officially passed Proposal 106 as of April 10 at 20:00 UTC+8. According to ChainCatcher, the mainnet has adjusted the behavior and execution cost of the SELFDESTRUCT instruction. Contracts will only be permanently removed from the blockchain if the instruction is called within the same transaction as the contract's creation. Otherwise, executing the instruction will merely transfer the assets within the contract to a specified address, without deleting the contract itself. Additionally, the energy consumption for SELFDESTRUCT has been changed from 0 to 5000. This adjustment aligns TRON's mechanisms more closely with Ethereum, enhancing the compatibility of the TRON Virtual Machine (TVM). It aims to provide more stable foundational support for multi-chain development and ecosystem adaptation. #TRON#Proposal106#Blockchain#Ethereum#TVM#SELFDESTRUCT#Mainnet#MultiChain#Ecosystem#Crypto#ETH#TRX

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