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Source channel @githubtrending · Post #14815 · Jun 10

#jupyter_notebook#chatglm#chatglm3#gemma_2b_it#glm_4#internlm2#llama3#llm#lora#minicpm#q_wen#qwen#qwen1_5#qwen2 This guide helps beginners set up and use open-source large language models (LLMs) on Linux or cloud platforms like AutoDL, with step-by-step instructions for environment setup, model deployment, and fine-tuning for models such as LLaMA, ChatGLM, and InternLM[2][4][5]. It covers everything from basic installation to advanced techniques like LoRA and distributed fine-tuning, and supports integration with tools like LangChain and online demo deployment. The main benefit is making powerful AI models accessible and easy to use for students, researchers, and anyone interested in experimenting with or customizing LLMs for their own projects[2][4][5]. https://github.com/datawhalechina/self-llm

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Crypto M - Crypto News

@CryptoM · Post #64776 · 04/09/2026, 10:11 PM

🚀 CFTC and DOJ Legal Actions Could Influence Future of Prediction Markets The Commodity Futures Trading Commission (CFTC) and the Department of Justice (DOJ) have initiated legal proceedings against the states of Arizona, Connecticut, and Illinois concerning their actions against CFTC-registered prediction markets. According to NS3.AI, a recent 2-1 ruling by the Third Circuit Court upheld an injunction preventing New Jersey from applying its gambling laws to Kalshi, a prediction market platform. The court determined that Kalshi's contracts related to sports events are classified as swaps under the Commodity Exchange Act, thereby falling under the exclusive jurisdiction of the CFTC. This legal dispute has the potential to significantly influence the regulatory framework for decentralized prediction markets and crypto-native derivatives across the United States. #CFTC#DOJ#PredictionMarkets#Kalshi#CommodityExchangeAct#Regulation#CryptoDerivatives#USLaw#LegalActions#DecentralizedFinance