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What is Zyphra Zonos?

Zyphra is excited to announce the beta launch of Zonos-v0.1, featuring two advanced and real-time text-to-speech models that incorporate high-fidelity voice cloning technology. This release includes a 1.6B transformer model and a 1.6B hybrid model, both distributed under the Apache 2.0 license. Considering the difficulties in measuring audio quality quantitatively, we assert that the quality of output generated by Zonos matches or exceeds that of leading proprietary TTS systems currently on the market. Moreover, we believe that providing access to such high-quality models will significantly enhance progress in TTS research. The model weights for Zonos are readily available on Huggingface, along with sample inference code hosted in our GitHub repository. In addition, Zonos can be accessed through our model playground and API, which offers simple and competitive flat-rate pricing options for users. To showcase Zonos's performance, we have compiled a series of sample comparisons against existing proprietary models that illustrate its exceptional capabilities. This project underscores our dedication to promoting innovation within the text-to-speech technology sector, and we anticipate that it will inspire further advancements in the field.

What is Timestral?

Timestral is a comprehensive suite of time-series foundation models accompanied by a Python inference toolkit, specifically designed to enable the creation of multivariate probabilistic forecasts derived from historical data sequences. It offers four distinct model sizes, including 5M, 28M, 123M, and 209M parameters, each capable of managing past-only, known-future, and categorical covariates, while providing quantile forecasts that can accommodate context windows of up to 32,768 time steps. Users can conveniently load pretrained weights from the Hugging Face Hub or from their local files, allowing for inference on both CPU and GPU setups. These forecasts can be integrated effortlessly into a wide array of applications, such as monitoring systems, capacity planning, energy management, supply chain logistics, financial risk analysis, and maintenance operations. Additionally, Timestral boasts zero-shot forecasting capabilities and can be customized to specific domain data using the Mistral Forge, further enhancing its versatility. This toolkit primarily targets data scientists, machine learning engineers, and collaborative teams eager to devise effective forecasting solutions; its repository code is available under the Apache 2.0 license, while the model weights are managed by a distinct Modified MIT license. With its robust and comprehensive features, Timestral is set to considerably improve the precision and effectiveness of predictive analytics across various sectors, ensuring that users can make informed decisions based on reliable forecasts. As industries increasingly rely on data-driven insights, Timestral stands out as an essential resource for achieving superior forecasting outcomes.

Media

Media

No images available

Integrations Supported

GitHub
Hugging Face

Integrations Supported

Mistral Forge

API Availability

Has API

API Availability

Has API

Pricing Information

$0.02 per minute
Free Trial Offered?

Pricing Information

Pricing not provided
Free Version

Supported Platforms

SaaS

Supported Platforms

On-Prem

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Zyphra

Company Location

United States

Company Website

www.zyphra.com/post/beta-release-of-zonos-v0-1

Company Facts

Organization Name

Mistral AI

Date Founded

2023

Company Location

France

Company Website

github.com/mistralai/timestral

Categories and Features

AI Models

Not specified

AI Voice Models

Not specified

Text to Speech

Not specified

Voice Cloning

Not specified

Categories and Features

AI Models

Not specified

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