LLaMA explained: KV-Cache, Rotary Positional Embedding, RMS Norm, Grouped Query Attention, SwiGLU

Transformer Architecture: Fast Attention, Rotary Positional Embeddings, and Multi-Query Attention

TensorFlow Transformer model from Scratch (Attention is all you need)

Efficient Inference of Extremely Large Transformer Models

LongNet: Scaling Transformers to 1,000,000,000 tokens: Python Code + Explanation

Coding a Transformer from scratch on PyTorch, with full explanation, training and inference.

Injecting Transformer Models with Steroids (Paper Breakdown)

Session 10: ML Foundations Course - PyTorch & TensorFlow Models with Driverless AI

Coding Stable Diffusion from scratch in PyTorch

Implement Llama 3 From Scratch - PyTorch

Matrix Multiplication Part 3 || Dealing With Tensor Shape Errors

Mistral Architecture Explained From Scratch with Sliding Window Attention, KV Caching Explanation

I implement DALLE 1 from SCRATCH on MNIST

Training a LLaMA in your Backyard: Fine-tuning Very Large... - Sourab Mangrulkar & Younes Belkada

Efficient LLM Inference (vLLM KV Cache, Flash Decoding & Lookahead Decoding)

Implement BERT From Scratch - PyTorch

BERT Architecture Implementation from Scratch

MIT 6.S191 (2023): Deep Learning New Frontiers

Llama - EXPLAINED!

Implementing GPT-2 From Scratch (Transformer Walkthrough Part 2/2)