Search Results for "audio text sync"
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9 projects for "audio text sync" with 2 filters applied:
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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v2ray-rules-dat
V2Ray routing rules file enhanced version, which can replace V2Ray
v2ray-rules-dat is a repository that compiles and distributes enhanced rule data (domain lists, geo-IP/geo-domain data, block/proxy/detect lists) intended for use with tools like V2Ray, Xray-core, and similar network/proxy frameworks. The dataset serves as an alternative or supplement to official geoip/ geosite data files, often providing more up-to-date, community-curated entries — enabling better routing, blocking, or traffic management when using those proxy tools. The repository is... -
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Flutter Rust Bridge
Rust binding generator, feature-rich, but seamless and simple
flutter_rust_bridge is a toolchain that generates ergonomic bindings between Rust and Dart/Flutter so you can write performance-critical logic in Rust while building UI in Flutter. It abstracts away the low-level FFI details, letting developers define Rust functions and data structures that are safely callable from Dart. The project supports passing complex types, handling async operations and streams, and integrating with Flutter across mobile and desktop targets. By leaning on Rust’s... -
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OmniTools
Self-hosted collection of powerful web-based tools for everyday tasks
...A key design choice is that file processing happens entirely on the client side, meaning your data stays in your browser instead of being sent to the backend. The tool catalog spans both technical and non-technical needs, including image, video, audio, PDF, text, date/time, math, and data format utilities like JSON/CSV/XML helpers. It’s also packaged for straightforward self-hosting, with a lightweight Docker image and simple run commands, so it can be deployed quickly on a homelab or internal network. -
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GenAI Processors
GenAI Processors is a lightweight Python library
GenAI Processors is a lightweight Python library for building modular, asynchronous, and composable AI pipelines around Gemini. Its central abstraction is the Processor, a unit of work that consumes an asynchronous stream of parts (text, images, audio, JSON) and produces another stream, making it natural to chain operations and keep everything streaming end-to-end. Processors can be composed sequentially (to build multi-step flows) or in parallel (to fan-out work and merge results), which makes sophisticated agent behaviors easy to express with simple operators. ... -
Demo Series - Small Business Backup By VeeamWatch this on-demand demo series and learn how to protect your Microsoft 365 data with clear, simple, actionable steps that are easy to implement for businesses of all sizes.
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LLM Tornado
The .NET library to build AI agents with 30+ built-in connectors
...The framework introduces a powerful orchestration system based on graph-like structures, where agents, tasks, and transitions can be defined and executed in parallel or sequential flows. It supports multimodal inputs and outputs, including text, images, audio, and documents, making it suitable for a wide range of AI applications. LLMTornado also integrates advanced protocols such as Model Context Protocol and agent-to-agent communication, enabling complex interactions between systems. With built-in support for local deployments, enterprise guardrails, and observability features. -
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Multimodal
TorchMultimodal is a PyTorch library
This project, also known as TorchMultimodal, is a PyTorch library for building, training, and experimenting with multimodal, multi-task models at scale. The library provides modular building blocks such as encoders, fusion modules, loss functions, and transformations that support combining modalities (vision, text, audio, etc.) in unified architectures. It includes a collection of ready model classes—like ALBEF, CLIP, BLIP-2, COCA, FLAVA, MDETR, and Omnivore—that serve as reference implementations you can adopt or adapt. The design emphasizes composability: you can mix and match encoder, fusion, and decoder components rather than starting from monolithic models. ... -
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AudioCraft
Audiocraft is a library for audio processing and generation
AudioCraft is a PyTorch library for text-to-audio and text-to-music generation, packaging research models and tooling for training and inference. It includes MusicGen for music generation conditioned on text (and optionally melody) and AudioGen for text-conditioned sound effects and environmental audio. Both models operate over discrete audio tokens produced by a neural codec (EnCodec), which acts like a tokenizer for waveforms and enables efficient sequence modeling. ... -
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ftdetector
File type detector library
...It uses hash tables to make the detection of a file type as fast as possible. The signature and mime types lists are stored at simple user-friendly files. This file type detector supports a lot of formats (image, archive, text, documents, audio, video, fonts and others). It also includes Microsoft OLE compound file types. The detector's algorythm has special features to detect text file types like (HTML, XML, JSON, etc.) and text file UNICODE charsets by using their BOMs (Byte order marks). Its small simple interface can be used at the most popular platforms. -
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go-rock-libraries-showcases
Comprehensive tutorial that integrates blogs, examples, audio, video
...It is designed for learners who have already finished Go, and want to deepen their skills by exploring real-world libraries that are popular and highly regarded in the Go ecosystem. The course uses a “three-in-one” approach: blog posts, code examples, and audio/video lectures are combined to explain each library in practical context. The README explains that the motivation is the sheer number of powerful libraries that many developers do not have time to evaluate, so the course highlights a subset of “rock star” libraries and shows how to use them effectively. The basic information section lists the instructor, prerequisites (basic Go ability, preferably completion of the fundamentals course), and the development environment: Go 1.2–1.4, Sublime Text 3, and macOS 10.9–10.10. -
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