flash-attention VS DeepSpeed

Compare flash-attention vs DeepSpeed and see what are their differences.

flash-attention

Fast and memory-efficient exact attention (by Dao-AILab)

DeepSpeed

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. (by microsoft)
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flash-attention DeepSpeed
25 51
10,263 32,055
8.8% 3.1%
9.4 9.8
2 days ago 4 days ago
Python Python
BSD 3-clause "New" or "Revised" License 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.

flash-attention

Posts with mentions or reviews of flash-attention. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-10.

DeepSpeed

Posts with mentions or reviews of DeepSpeed. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-06.

What are some alternatives?

When comparing flash-attention and DeepSpeed you can also consider the following projects:

ColossalAI - Making large AI models cheaper, faster and more accessible

Megatron-LM - Ongoing research training transformer models at scale

fairscale - PyTorch extensions for high performance and large scale training.

TensorRT - NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.

xformers - Hackable and optimized Transformers building blocks, supporting a composable construction.

accelerate - 🚀 A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision

fairseq - Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

mesh-transformer-jax - Model parallel transformers in JAX and Haiku

llama - Inference code for Llama models

text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.

server - The Triton Inference Server provides an optimized cloud and edge inferencing solution.