RHO-Loss VS flash-attention

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


Fast and memory-efficient exact attention (by HazyResearch)
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RHO-Loss flash-attention
1 15
143 2,107
3.5% 25.2%
5.5 8.2
6 months 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.


Posts with mentions or reviews of RHO-Loss. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-08-14.


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 2023-03-15.

What are some alternatives?

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

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"

TensorRT - NVIDIA® TensorRT™, an SDK for high-performance deep learning inference, includes a deep learning inference optimizer and runtime that delivers low latency and high throughput for inference applications.

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.

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

RWKV-v2-RNN-Pile - RWKV-v2-RNN trained on the Pile. See https://github.com/BlinkDL/RWKV-LM for details.


kernl - Kernl lets you run PyTorch transformer models several times faster on GPU with a single line of code, and is designed to be easily hackable.

flash-attention-jax - Implementation of Flash Attention in Jax

CodeRL - This is the official code for the paper CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning (NeurIPS22).

google-research - Google Research

GFPGAN - GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.