Allow it to be injected into the roof of your mouth and it will grow into your brain, allow you to connect with others without even picking up your phone. Its followers are growing. Its detractors say it is a cult. But for one journalist, hired to do a puff-piece interview with their CEO, it will change the world forever.Adan just wants to stay at home with his smart-companion Elegy - phone, friend, confidante, sex toy. But when his mother flees to Europe and joins a cult, leaving him penniless, he has to enlist in the army. Sentient robots are invading America, but it seems Adan has a surprising ability to survive their attacks. He has a purpose, even if he doesn't know what it is.And in the far future, war between a hivemind of Ais and the remnants of humanity is coming to its inevitable end. But one woman has developed a weapon which might change the course of the war. It's just a pity she's trapped in an inescapable prison on a hivemind ship.

    Unfortunately, his actions result in him getting press-ganged into an expendable crew of misfits recruited by a legendary starship captain. Their mission? To recover a collection of lost sun-destroying missiles that could restart a galactic war. Unfortunately, Vance is smart enough to know something is wrong with this picture. After all, no sane person would recruit this crew to save the universe.SPACE ACADEMY DROPOUTS is an all-new series from C.T. Phipps (Supervillainy Saga, Agent G) and Michael Suttkus (I Was a Teenage Weredeer, Lucifer's Star) that lampoons the space opera as well as military science fiction genres.

    If you're a data scientist or machine learning engineer, this practical book shows you how to train and scale these large models using HuggingFace Transformers, a Python-based deep learning library.Transformers have been used to write realistic news stories, improve Google Search queries, and even create chatbots that tell corny jokes. In this guide, authors Lewis Tunstall, Leandro von Werra, and Thomas Wolf use a hands-on approach to teach you how Transformers work and how to integrate them in your applications. You'll quickly learn a variety of tasks they can help you solve.* Build, debug, and optimize Transformer models for core NLP tasks, such as text classification, named entity recognition, and question answering* Learn how Transformers can be used for cross-lingual transfer learning* Apply Transformers in real-world scenarios where labeled data is scarce* Make Transformer models efficient for deployment using techniques such as distillation, pruning, and quantization* Train Transformers from scratch and learn how to scale to multiple GPUs and distributed environments