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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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AppPie

@AppPie · Post #2291 · 12/31/2024, 04:02 AM

#Developers Shortest: AI 驱动的自然语言测试框架 🔗GitHub Shortest 是一个基于 Playwright 的端到端测试框架,允许你用自然语言编写测试用例,由 AI 处理具体实现。 主要特点 • 自然语言测试:用日常语言描述测试场景 • AI 驱动执行:使用 Claude API 处理测试实现 • Playwright 基础:稳定可靠的测试执行 • GitHub 集成:支持双因素认证 • 邮件验证:集成 Mailosaur 开源许可证 MIT license。 #GitHub#OpenSource#Testing#AutomatedTesting#AI#Playwright 📮 频道 @AppPie​​​​​​​​​​​​​​​​