Transformers explained | The architecture behind LLMs скачать в хорошем качестве

Transformers explained | The architecture behind LLMs

All you need to know about the transformer architecture: How to structure the inputs, attention (Queries, Keys, Values), positional embeddings, residual connections. Bonus: an overview of the difference between Recurrent Neural Networks (RNNs) and transformers. 9:19 Order of multiplication should be the opposite: x1(vector) * Wq(matrix) = q1(vector). Otherwise we do not get the 1x3 dimensionality at the end. Sorry for messing up the animation! Check this out for a super cool transformer visualisation! 👏 https://poloclub.github.io/transforme... ➡️ AI Coffee Break Merch! 🛍️ https://aicoffeebreak.creator-spring.... Outline: 00:00 Transformers explained 00:47 Text inputs 02:29 Image inputs 03:57 Next word prediction / Classification 06:08 The transformer layer: 1. MLP sublayer 06:47 2. Attention explained 07:57 Attention vs. self-attention 08:35 Queries, Keys, Values 09:19 Order of multiplication should be the opposite: x1(vector) * Wq(matrix) = q1(vector). 11:26 Multi-head attention 13:04 Attention scales quadratically 13:53 Positional embeddings 15:11 Residual connections and Normalization Layers 17:09 Masked Language Modelling 17:59 Difference to RNNs Thanks to our Patrons who support us in Tier 2, 3, 4: 🙏 Dres. Trost GbR, Siltax, Vignesh Valliappan, ‪@Mutual_Information‬ , Kshitij Our old Transformer explained 📺 video:    • The Transformer neural network architectur...   📺 Tokenization explained:    • What is tokenization and how does it work?...   📺 Word embeddings:    • How modern search engines work – Vector da...   📽️ Replacing Self-Attention:    • Replacing Self-attention   📽️ Position embeddings:    • Position encodings in Transformers explain...   ‪@SerranoAcademy‬ Transformer series:    • The Attention Mechanism in Large Language ...   📄 Vaswani, Ashish, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Łukasz Kaiser, and Illia Polosukhin. "Attention is all you need." Advances in neural information processing systems 30 (2017). ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀ 🔥 Optionally, pay us a coffee to help with our Coffee Bean production! ☕ Patreon:   / aicoffeebreak   Ko-fi: https://ko-fi.com/aicoffeebreak ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀ 🔗 Links: AICoffeeBreakQuiz:    / aicoffeebreak   Twitter:   / aicoffeebreak   Reddit:   / aicoffeebreak   YouTube:    / aicoffeebreak   #AICoffeeBreak #MsCoffeeBean #MachineLearning #AI #research​ Music 🎵 : Sunset n Beachz - Ofshane Video editing: Nils Trost