#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
Bitcoin ETFs See Major Inflow Reversal
On January 15, Bitcoin spot ETFs recorded a net inflow of $755 million, marking the first inflow after four days of outflows. The Fidelity ETF (FBTC) led the charge, attracting $463 million. Meanwhile, Ethereum products also saw inflows, totaling $59.78 million.
Forecasts from HashKey Group predict Bitcoin could hit $300,000 by 2025 and Ethereum $8,000, with overall market cap reaching $10 trillion. Analyst insights suggest the Litecoin ETF may be next for approval in the US.
For more details, visit the link.
#Bitcoin#ETF#Cryptocurrency#Ethereum#Investing#Finance#MarketTrends#HashKey#Litecoin#Fidelity#CryptoForecast#AI#VC