Unify Efficient Fine-Tuning of 100+ LLMs
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Updated
Jun 12, 2024 - Python
Unify Efficient Fine-Tuning of 100+ LLMs
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Official LISTEN.moe Android app
Tutel MoE: An Optimized Mixture-of-Experts Implementation
MindSpore online courses: Step into LLM
[Preprint] Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer Models
An unofficial https://bgm.tv ui first app client for Android and iOS, built with React Native. 一个无广告、以爱好为驱动、不以盈利为目的、专门做 ACG 的类似豆瓣的追番记录,bgm.tv 第三方客户端。为移动端重新设计,内置大量加强的网页端难以实现的功能,且提供了相当的自定义选项。 目前已适配 iOS / Android / WSA、mobile / 简单 pad、light / dark theme、移动端网页。
[arXiv'24] Multilinear Mixture of Experts: Scalable Expert Specialization through Factorization
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Implementation of MoE Mamba from the paper: "MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts" in Pytorch and Zeta
Implementation of the "the first large-scale multimodal mixture of experts models." from the paper: "Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts"
Implementation of Switch Transformers from the paper: "Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity"
Mixture-of-Experts for Large Vision-Language Models
This is the repo for the MixKABRN Neural Network (Mixture of Kolmogorov-Arnold Bit Retentive Networks), and an attempt at first adapting it for training on text, and later adjust it for other modalities.
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