GitHub地址:https://github.com/state-spaces/mamba 论文标题:Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality 本文目的在于学术交流,并不代表本公众号赞同其观点或对其内容真实性负责,版权归原作者所有,如有侵权请告知删除。
论文地址：https://arxiv.org/pdf/2405.21060GitHub 地址：https://github.com/state-spaces/mamba论文标题：Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality 总体而言，本文提出了 SSD（state space duality）框架，基于此，研究者设计了一个新的体系架构 M...
psikosen/mamba2main 1 Branch 0 Tags Code This branch is 88 commits behind state-spaces/mamba:main.Folders and filesLatest commit tridao Merge pull request state-spaces#42 from jmercat/main 711b89f· Dec 9, 2023 History15 Commits .github/workflows First release Dec 5, 2023...
Installlm-evaluation-harness:pip install -e 3rdparty/lm-evaluation-harness. On Python 3.10 you might need to manually install the latest version ofpromptsource:pip install git+https://github.com/bigscience-workshop/promptsource.git. Run evaluation with (more documentation at thelm-evaluation-harnes...
这次，新一代的Mamba-2卷土重来、再战顶会，顺利拿下了ICML 2024！仍是前作的两位大佬（换了个顺序），仍是熟悉的配方：论文地址：https://arxiv.org/pdf/2405.21060 开源代码和模型权重：https://github.com/state-spaces/mamba 不同的是，作者在更高的视角上，统一了状态空间模型（SSM）和注意力机制（...
Official implementation of Phi-Mamba. A MOHAWK-distilled model (Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models) - use current mamba2 implementation · goombalab/phi-mamba@dd8c3b7
对Mamba-2模型或者状态空间二元性理论感兴趣的，可以读起来了～博客（两个地址内容一样）：https://tridao.me/blog/https://goombalab.github.io/blog/ 论文：https://arxiv.org/abs/2405.21060 代码和模型权重：https://github.com/state-spaces/mamba 参考链接：[1]https://x.com/_albertgu/status/...
Minimal Mamba-2 implementation in PyTorch. Contribute to tommyip/mamba2-minimal development by creating an account on GitHub.
1. Install `lm-evaluation-harness` by `pip install lm-eval==0.4.2`. 2. Run evaluation with (more documentation at the [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness/tree/big-refactor) repo): ``` ``` sh lm_eval --model mamba_ssm --model_args pretrained...
git clone https://github.com/YuHengsss/VSSD.gitcdVSSD Step 2: Environment Setup: Create and activate a new conda environment conda create -n VSSD conda activate VSSD Install Dependencies pip install -r requirements.txt Dependencies forDetectionandSegmentation(optional) ...