PyTorch-Guide VS TransformerEngine

Compare PyTorch-Guide vs TransformerEngine and see what are their differences.

TransformerEngine

A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper and Ada GPUs, to provide better performance with lower memory utilization in both training and inference. (by NVIDIA)
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PyTorch-Guide TransformerEngine
2 2
23 1,450
- 6.4%
1.8 9.5
over 2 years ago 6 days ago
Python Python
- Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

PyTorch-Guide

Posts with mentions or reviews of PyTorch-Guide. We have used some of these posts to build our list of alternatives and similar projects.

TransformerEngine

Posts with mentions or reviews of TransformerEngine. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-01-18.

What are some alternatives?

When comparing PyTorch-Guide and TransformerEngine you can also consider the following projects:

halutmatmul - Hashed Lookup Table based Matrix Multiplication (halutmatmul) - Stella Nera accelerator

Whisper - High-performance GPGPU inference of OpenAI's Whisper automatic speech recognition (ASR) model

NeuralCDE - Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)

autocvd - Tool to automatically set CUDA_VISIBLE_DEVICES based on GPU utilization. Usable from command line and code.

cog - Containers for machine learning

warp-drive - Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)

bittensor - Internet-scale Neural Networks

ivy - The Unified AI Framework

nanoGPT - The simplest, fastest repository for training/finetuning medium-sized GPTs.

fastaudio - 🔊 Audio and fastai v2

liberate-fhe - A Fully Homomorphic Encryption (FHE) library for bridging the gap between theory and practice with a focus on performance and accuracy.

FastFold - Optimizing AlphaFold Training and Inference on GPU Clusters