Foundational Models for State-of-the-Art Speech and Text Translation SeamlessM4T SeamlessM4T is designed to provide high quality translation, allowing people from different linguistic communities to communicate effortlessly through speech and text. SeamlessM4T covers: 📥 101 languages for speech input. ⌨️ 96 Languages for text input/output. 🗣️ 35 languages for speech output. This unified model enables multiple tasks without relying on multiple separate models: Speech-to-speech translation (S2…
Provides an efficient allocation free async/await integration for Unity.UniTask Provides an efficient allocation free async/await integration for Unity. Struct based UniTask<T> and custom AsyncMethodBuilder to achieve zero allocation Makes all Unity AsyncOperations and Coroutines awaitable PlayerLoop based task(UniTask.Yield, UniTask.Delay, UniTask.DelayFrame, etc..) that enable replacing all coroutine operations MonoBehaviour Message Events and uGUI Events as awaitable/async-enumerab…
This repository is for active development of the Azure SDK for Go. For consumers of the SDK we recommend visiting our public developer docs at:Azure SDK for Go This repository is for active development of the Azure SDK for Go. For consumers of the SDK you can follow the links below to visit the documentation you are interested in Overview of Azure SDK for Go SDK Reference Code Samples for Azure Go SDK Azure REST API Docs General Azure Docs Share your feedback to our Azure SDK Getting Started…
Advanced Subscription Manager for QX, Loon, Surge, Stash and ShadowRocket! Sub-Store Advanced Subscription Manager for QX, Loon, Surge, Stash and ShadowRocket. Core functionalities: Conversion among various formats. Subscription formatting. Collect multiple subscriptions in one URL. 1. Subscription Conversion Supported Input Formats SS URI SSR URI SSD URI V2RayN URI QX (SS, SSR, VMess, Trojan, HTTP) Loon (SS, SSR, VMess, Trojan, HTTP) Surge (SS, VMess, Trojan, HTTP) Sta…
Code for Stanford CS224uCS224u: Natural Language Understanding Code for the Stanford course. Spring 2023 Christopher Potts Core components setup.ipynb Details on how to get set up to work with this code. hw_*.ipynb The set of homeworks for the current run of the course. tutorial_* notebooks Introductions to Juypter notebooks, scientific computing with NumPy and friends, and PyTorch. torch_*.py modules A generic optimization class (torch_model_base.py) and subclasses for GloVe, Autoencoders, sha…
This repo hosts the official MediaPipe samples with a goal of showing the fundamental steps involved to create apps with our machine learning platform. External PRs for fixes are welcome, however new sample/demo PRs will likely be rejected to maintain the simplicity of this repo for ongoing maintenance. It is strongly recommended that contributors who are interested in submitting more complex samples or demos host their samples in their own public repos and create written tutorials to share wit…
If tinygrad wasn't small enough for you...
Official Go Implementation of the Quai NetworkGo Quai Official Golang implementation of the Quai protocol. Building the source For prerequisites and detailed build instructions please read the Installation Instructions. First, clone the repository and navigate to it using $ git clone https://github.com/dominant-strategies/go-quai.git $ cd go-quai Next, you will need to copy some default environment variables to your machine. You can do this by running $ cp network.env.dist network.env Buildi…
The image prompt adapter is designed to enable a pretrained text-to-image diffusion model to generate images with image prompt.IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models Project Page | Paper (ArXiv) Introduction we present IP-Adapter, an effective and lightweight adapter to achieve image prompt capability for the pre-trained text-to-image diffusion models. An IP-Adapter with only 22M parameters can achieve comparable or even better performance to a fi…