У нас вы можете посмотреть бесплатно Chain-of-thought prompting - Explained! или скачать в максимальном доступном качестве, которое было загружено на ютуб. Для скачивания выберите вариант из формы ниже:
Если кнопки скачивания не
загрузились
НАЖМИТЕ ЗДЕСЬ или обновите страницу
Если возникают проблемы со скачиванием, пожалуйста напишите в поддержку по адресу внизу
страницы.
Спасибо за использование сервиса ClipSaver.ru
Let's talk about how language models can reason with chain-of-though prompting A parameter efficient fine tuning technique that makes use of a low rank adapter to (1) reduce storage required per task by decreasing the number of trainable parameters added to the network per task (2) remove inference latency ensuring the stored parameters are applied to the existing network architecture instead of adding more RESOURCES [1 📚] Paper with Chain-of-thought prompting: https://arxiv.org/pdf/2201.11903 [2 📚] Paper that introduced GPT-3: https://arxiv.org/pdf/2005.14165 ABOUT ME ⭕ Subscribe: https://www.youtube.com/c/CodeEmporiu... 📚 Medium Blog: / dataemporium 💻 Github: https://github.com/ajhalthor 👔 LinkedIn: / ajay-halthor-477974bb PLAYLISTS FROM MY CHANNEL ⭕ Deep Learning 101: • Deep Learning 101 ⭕ Natural Language Processing 101: • Natural Language Processing 101 ⭕ Reinforcement Learning 101: • Reinforcement Learning 101 Natural Language Processing 101: • Natural Language Processing 101 ⭕ Transformers from Scratch: • Natural Language Processing 101 ⭕ ChatGPT Playlist: • ChatGPT MATH COURSES (7 day free trial) 📕 Mathematics for Machine Learning: https://imp.i384100.net/MathML 📕 Calculus: https://imp.i384100.net/Calculus 📕 Statistics for Data Science: https://imp.i384100.net/AdvancedStati... 📕 Bayesian Statistics: https://imp.i384100.net/BayesianStati... 📕 Linear Algebra: https://imp.i384100.net/LinearAlgebra 📕 Probability: https://imp.i384100.net/Probability OTHER RELATED COURSES (7 day free trial) 📕 ⭐ Deep Learning Specialization: https://imp.i384100.net/Deep-Learning 📕 Python for Everybody: https://imp.i384100.net/python 📕 MLOps Course: https://imp.i384100.net/MLOps 📕 Natural Language Processing (NLP): https://imp.i384100.net/NLP 📕 Machine Learning in Production: https://imp.i384100.net/MLProduction 📕 Data Science Specialization: https://imp.i384100.net/DataScience 📕 Tensorflow: https://imp.i384100.net/Tensorflow CHAPTERS 0:00 Introduction 1:02 Why CoT prompting? 2:05 Few Shot Learning 3:57 Reasoning 5:55 What is Chain of Thought? 6:09 Performance & benefits 7:07 Quiz 8:13 Conclusion