Unify Efficient Fine-Tuning of 100+ LLMs
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Updated
May 18, 2024 - Python
Unify Efficient Fine-Tuning of 100+ LLMs
An unofficial https://bgm.tv 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。
Official LISTEN.moe Android app
Mixture-of-Experts for Large Vision-Language Models
⭐ Moe-Counter Compatible Website Hit Counter Written in Gleam
Tutel MoE: An Optimized Mixture-of-Experts Implementation
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.
japReader is an app for breaking down Japanese sentences and tracking vocabulary progress
中文Mixtral混合专家大模型(Chinese Mixtral MoE LLMs)
Community Implementation of the paper: "Multi-Head Mixture-of-Experts" In PyTorch
Node JS enka.network API wrapper written on TypeScript which provides localization, caching and convenience.
PyTorch Re-Implementation of "The Sparsely-Gated Mixture-of-Experts Layer" by Noam Shazeer et al. https://arxiv.org/abs/1701.06538
A simple project that help visualize expert router choices for text generation
Official repository for paper "MATERobot: Material Recognition in Wearable Robotics for People with Visual Impairments" at ICRA 2024, Best Paper Finalist on Human-Robot Interaction
ModuleFormer is a MoE-based architecture that includes two different types of experts: stick-breaking attention heads and feedforward experts. We released a collection of ModuleFormer-based Language Models (MoLM) ranging in scale from 4 billion to 8 billion parameters.
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