Coding LLaMA 2 from scratch in PyTorch - KV Cache, Grouped Query Attention, Rotary PE, RMSNorm Published 2023-09-02 Download video MP4 360p Download video MP4 720p Recommendations 1:10:55 LLaMA explained: KV-Cache, Rotary Positional Embedding, RMS Norm, Grouped Query Attention, SwiGLU 26:55 LoRA: Low-Rank Adaptation of Large Language Models - Explained visually + PyTorch code from scratch 08:22 Python Session 4 - 26th May 2024 55:55 Miles Cranmer - The Next Great Scientific Theory is Hiding Inside a Neural Network (April 3, 2024) 50:55 Quantization explained with PyTorch - Post-Training Quantization, Quantization-Aware Training 06:14 Mamba Language Model Simplified In JUST 5 MINUTES! 58:04 Attention is all you need (Transformer) - Model explanation (including math), Inference and Training 14:06 RoPE (Rotary positional embeddings) explained: The positional workhorse of modern LLMs 37:01 TransformerFAM: Feedback attention is working memory 11:17 Rotary Positional Embeddings: Combining Absolute and Relative 1:26:21 Mistral / Mixtral Explained: Sliding Window Attention, Sparse Mixture of Experts, Rolling Buffer 08:33 The KV Cache: Memory Usage in Transformers 54:52 BERT explained: Training, Inference, BERT vs GPT/LLamA, Fine tuning, [CLS] token 1:15:39 Kolmogorov-Arnold Networks: MLP vs KAN, Math, B-Splines, Universal Approximation Theorem 11:00 Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention 49:24 Retrieval Augmented Generation (RAG) Explained: Embedding, Sentence BERT, Vector Database (HNSW) 1:27:41 Programming in Modern C with a Sneak Peek into C23 - Dawid Zalewski - ACCU 2023 10:31 The U-Net (actually) explained in 10 minutes 1:00:49 The Art of Code - Dylan Beattie Similar videos 08:13 Variants of Multi-head attention: Multi-query (MQA) and Grouped-query attention (GQA) 00:54 Code LLAMA 2: Your AI Coding Genius | TrendSpark AI 05:35 Train Llama 2 from Scratch in PyTorch Locally 2:59:24 Coding a Transformer from scratch on PyTorch, with full explanation, training and inference. 01:21 Transformer Architecture: Fast Attention, Rotary Positional Embeddings, and Multi-Query Attention 2:57:16 LLAMA 2 Full Paper Explained 5:03:32 Coding Stable Diffusion from scratch in PyTorch 33:33 Getting to Know Llama 2: Everything You Need to Start Building 00:48 Perplexity's AI Search & Code Llama Chat#llama #perplexity 39:10 Mistral Architecture Explained From Scratch with Sliding Window Attention, KV Caching Explanation 08:48 Karpathy's Llama2.c - Quick Look for Beginners 09:53 Llama 2 Paper Explained 08:31 Code Llama Paper Explained More results