#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
📊 ETFs | Weekly Flows Snapshot
SOL ETFs were the only ones with net inflows among the top 3 this week.
#ETF#Flows#Markets
#BTC#ETH#SOL#Crypto
———
結構解讀關鍵👇🥇資源搜索🖲️👆
📉 本週三大主流 ETF 資金流向出現明顯分化:
• BTC ETF:持續淨流出,賣壓集中於大型發行商
• ETH ETF:連續多日負流量,短線情緒偏保守
• SOL ETF:唯一錄得淨流入,資金逆勢布局
📈 結構解讀:
• 資金正在 避開高擁擠交易(BTC / ETH)
• SOL 成為短線輪動與主題交易承接標的
• ETF 流向顯示:市場並非全面風險退出,而是 選擇性進場
⚡️ 觀察重點:
若 SOL ETF 流入延續,可能代表
👉 資金正在測試「非 BTC / ETH 主流替代敘事」
👇⭐️👇
🤣留言分享觀點
🥲👇