perceiver-ar
By google-research
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| perceiver-ar | RHO-Loss | |
|---|---|---|
| 3 | 1 | |
| 225 | 173 | |
| 1.3% | 4.6% | |
| 0.0 | 0.0 | |
| 7 days ago | over 1 year ago | |
| Python | Python | |
| Apache License 2.0 | 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.
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.
perceiver-ar
Posts with mentions or reviews of perceiver-ar.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-08-14.
-
[D] Most important AI Paper´s this year so far in my opinion + Proto AGI speculation at the end
General-purpose, long-context autoregressive modeling with Perceiver AR - Deepmind 2022 Paper: https://arxiv.org/abs/2202.07765 Deepmind: https://www.deepmind.com/publications/perceiver-ar-general-purpose-long-context-autoregressive-generation Code: https://github.com/google-research/perceiver-ar
- GitHub - google-research/perceiver-ar
- [R] General-purpose, long-context autoregressive modeling with Perceiver AR - Deepmind 2022
RHO-Loss
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.
-
[D] Most important AI Paper´s this year so far in my opinion + Proto AGI speculation at the end
RHO-LOSS - Prioritized Training on Points that are Learnable, Worth Learning, and Not Yet Learnt - Trains Models 18x faster with higher accuracy Paper: https://arxiv.org/abs/2206.07137 Github: https://github.com/OATML/RHO-Loss
What are some alternatives?
When comparing perceiver-ar and RHO-Loss you can also consider the following projects:
flash-attention - Fast and memory-efficient exact attention
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).
EfficientZero - Open-source codebase for EfficientZero, from "Mastering Atari Games with Limited Data" at NeurIPS 2021.
XMem - [ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
msn - Masked Siamese Networks for Label-Efficient Learning (https://arxiv.org/abs/2204.07141)
DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
perceiver-ar vs flash-attention
RHO-Loss vs flash-attention-jax
perceiver-ar vs flash-attention-jax
RHO-Loss vs flash-attention
perceiver-ar vs CodeRL
RHO-Loss vs CodeRL
perceiver-ar vs EfficientZero
RHO-Loss vs EfficientZero
perceiver-ar vs XMem
RHO-Loss vs XMem
perceiver-ar vs msn
RHO-Loss vs DeepSpeed