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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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Host Testing and evaluation

@HostEvaluate · Post #853 · 01/18/2023, 12:02 PM

#misaka#DE#BER Host Provider: Misaka Network Location: Berlin, Germany Specification: 1vCore(Xeon Skylake) | 512MB RAM | 10GB NVMe | 512GB Traffic | $10.5 / Mo Test IP: 45.131.71.128 MTR: https://ping.sx/mtr?p=misaka-ber02-s2c 感谢商家提供的测试机。这款是 Misaka 新上的柏林机器,带 CN2 优化。应该会有活动的。这个 CN2 是从他们俄罗斯牵过去的,延迟比咸鱼云的法兰克福要低些。国际目前只有 retn, 后面会加 lumen, 具体啥时候加上就不得而知了。去往西欧延迟更低的一个选择。机器性能可以,本地带宽应该是 10Gbps? BerlinCN2Launch 年付 30off, 限 CN2 产品 https://paste.red/p/c20e1103c9f5