Optimizing Inference for Large Transformer Models 🧠
Optimizing the inference process for large Transformer models is key to reducing memory costs and operational latency in practice.
Sources lilianweng.github.io
Train Your Own LLM from Scratch with PyTorch
This repository provides scripts to implement and train a Transformer model from scratch using PyTorch, enabling you to build your own Large Language Model (LLM) with just a single GPU.
Sources github.com
Transformer Reparameterizations Lab announces series of new reparameterization techniques 🛠️
Transformer Reparameterizations Lab has released new reparameterization techniques to optimize training and inference performance for the Transformer architecture.
Sources x.com