DeepSpeed VS flash-attention

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

DeepSpeed

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. (by microsoft)

flash-attention

Fast and memory-efficient exact attention (by Dao-AILab)
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DeepSpeed flash-attention
51 25
31,510 9,618
3.4% 8.9%
9.8 9.5
1 day ago 5 days ago
Python Python
Apache License 2.0 BSD 3-clause "New" or "Revised" License
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.

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.

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.

What are some alternatives?

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

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

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

Megatron-LM - Ongoing research training transformer models at scale

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.