#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
🚨 BREAKING: $117M in assets stolen from @Balancer in the last 2 hours after a major hack!!!
🔹 Assets stolen are across multiple chains: #Ethereum, #Base, #Optimism, #Sonic, #Polygon, #Berachain – mainly in Liquid Staking Tokens (LSTs) of $ETH.
Top 5 stolen assets:
• 7,838 $WETH (~$29.1M)
• 6,841 $OSETH (~$26.8M)
• 4,459 $WSTETH (~$20.1M)
• 2,405 $SFRXETH (~$10M)
• 2,038 $RSETH (~$8.67M)
🔹 The hacker is acting quickly: Converting LSTs into $ETH in real-time!
🔹 Big move: Whale account 0x009, dormant for 3 YEARS, just resurfaced after the exploit and withdrew $7.38M worth of assets from #Balancer!
⚠️ ALERT: If you’re still on #Balancer, secure your funds NOW before it’s too late! 🔐
Follow @spotonchain for more updates about the hack!
https://x.com/spotonchain/status/1985289043383300351