Training LLM Models with Transformers

Alican Kiraz
4.7
12 izibuyekezo
I-Ebook
90
Amakhasi
Izilinganiso nezibuyekezo aziqinisekisiwe  Funda Kabanzi

Mayelana nale ebook

In our book, we explore in detail the working principles of artificial intelligence, LLM models, how these models can be trained, the training environment, how to prepare training data, and how to write the training code. We will learn in detail how to set up the training environment, use various Transformers libraries, train large LLM models through quantization (LoRA and QLoRA), create datasets in different formats, and grasp the mathematical foundations of artificial intelligence.

Izilinganiso nezibuyekezo

4.7
12 izibuyekezo

Mayelana nomlobi

Hi, I'm Alican. I have been working in the field of cybersecurity since 2015. In my early years, I developed my skills in Application Security and Bug Hunting. Since 2018, I have been specializing in Blue Team and Purple Team roles. Because I am passionate about cybersecurity, I have participated in numerous training programs and certification courses, and I currently hold 23 different professional certifications. Additionally, I have been involved in various projects in robotics, embedded systems, and artificial intelligence. I support the community on YouTube and Spotify Podcast with more than 50 research and training videos. I also have 2 books and 2 Udemy courses.

Nikeza le ebook isilinganiso

Sitshele ukuthi ucabangani.

Ulwazi lokufunda

Amasmathifoni namathebulethi
Faka uhlelo lokusebenza lwe-Google Play Amabhuku lwe-Android ne-iPad/iPhone. Livunyelaniswa ngokuzenzakalela ne-akhawunti yakho liphinde likuvumele ukuthi ufunde uxhunywe ku-inthanethi noma ungaxhunyiwe noma ngabe ukuphi.
Amakhompyutha aphathekayo namakhompyutha
Ungalalela ama-audiobook athengwe ku-Google Play usebenzisa isiphequluli sewebhu sekhompuyutha yakho.
Ama-eReaders namanye amadivayisi
Ukuze ufunde kumadivayisi e-e-ink afana ne-Kobo eReaders, uzodinga ukudawuniloda ifayela futhi ulidlulisele kudivayisi yakho. Landela imiyalelo Yesikhungo Sosizo eningiliziwe ukuze udlulise amafayela kuma-eReader asekelwayo.