flash-attention VS transformer-deploy

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

flash-attention

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

transformer-deploy

Efficient, scalable and enterprise-grade CPU/GPU inference server for 🤗 Hugging Face transformer models 🚀 (by ELS-RD)
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flash-attention transformer-deploy
25 8
10,263 1,609
8.8% 1.4%
9.4 6.8
2 days ago 5 months 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.

transformer-deploy

Posts with mentions or reviews of transformer-deploy. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-28.

What are some alternatives?

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

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

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

DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

memory-efficient-attention-pytorch - Implementation of a memory efficient multi-head attention as proposed in the paper, "Self-attention Does Not Need O(n²) Memory"

RWKV-LM - RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.

FasterTransformer - Transformer related optimization, including BERT, GPT

torch2trt - An easy to use PyTorch to TensorRT converter

alpaca_lora_4bit

TensorRT - PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT

OpenSeeFace - Robust realtime face and facial landmark tracking on CPU with Unity integration

XMem - [ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model