flash-attention-jax
| RHO-Loss | flash-attention-jax | |
|---|---|---|
| 1 | 1 | |
| 173 | 175 | |
| 4.6% | - | |
| 0.0 | 2.0 | |
| over 1 year ago | 2 months ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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RHO-Loss
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[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
flash-attention-jax
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[D] Most important AI Paper´s this year so far in my opinion + Proto AGI speculation at the end
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness Paper: https://arxiv.org/abs/2205.14135 Github: https://github.com/HazyResearch/flash-attention and https://github.com/lucidrains/flash-attention-jax
What are some alternatives?
flash-attention - Fast and memory-efficient exact attention
msn - Masked Siamese Networks for Label-Efficient Learning (https://arxiv.org/abs/2204.07141)
EfficientZero - Open-source codebase for EfficientZero, from "Mastering Atari Games with Limited Data" at NeurIPS 2021.
CodeRL - This is the official code for the paper CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning (NeurIPS22).
perceiver-ar
XMem - [ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
block-recurrent-transformer-pytorch - Implementation of Block Recurrent Transformer - Pytorch
DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.