CodeRL
This is the official code for the paper CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning (NeurIPS22). (by salesforce)
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| RHO-Loss | CodeRL | |
|---|---|---|
| 1 | 4 | |
| 173 | 476 | |
| 4.6% | 1.9% | |
| 0.0 | 4.2 | |
| over 1 year ago | 7 months 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.
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.
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
CodeRL
Posts with mentions or reviews of CodeRL.
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
CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning Paper: https://arxiv.org/pdf/2207.01780.pdf Github: https://github.com/salesforce/CodeRL
- AI Coding with CodeRL: Toward Mastering Program Synthesis with Deep RL
- [R] CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning
What are some alternatives?
When comparing RHO-Loss and CodeRL you can also consider the following projects:
flash-attention-jax - Implementation of Flash Attention in Jax
flash-attention - Fast and memory-efficient exact attention
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
perceiver-ar
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.