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Description
The QVAC SDK serves as a toolkit designed for developers looking to integrate on-device AI inference into their applications crafted with JavaScript/TypeScript or Python. It supplies a unified API to facilitate the execution of various supported language, vision, and speech models across both mobile and desktop platforms, encompassing features like model discovery and downloads, inference APIs, and optional connections to remote providers. With this toolkit, developers can create AI features that function offline, ensuring that prompts and processing occur directly on the device for local inference. Additionally, QVAC provides an OpenAI-compatible server alongside plugins that seamlessly link local models with developer tools. Aimed primarily at those developing AI-enhanced applications, the SDK's documentation outlines processes for setup, choosing models, handling tasks related to text generation, image, and audio, as well as invoking tools; the available functionalities can vary based on the chosen model and platform. Furthermore, the QVAC SDK is accessible as free, open-source software under the Apache 2.0 license, and using local inference does not necessitate a hosted QVAC account, making it even more appealing for developers. This flexibility and ease of use make the QVAC SDK a robust choice for integrating AI capabilities into modern applications.
Description
Timestral represents a suite of time-series foundation models along with a Python inference toolkit designed to create multivariate probabilistic forecasts based on historical data sequences. It comes in four different model sizes—5M, 28M, 123M, and 209M parameters—that are capable of handling past-only, known-future, and categorical covariates, providing quantile forecasts while accommodating context windows as extensive as 32,768 time steps. Users have the flexibility to load pretrained weights either from the Hugging Face Hub or directly from local files, enabling them to perform inference on both CPU and GPU. Such forecasts can be seamlessly integrated into various applications, including monitoring systems, capacity planning, energy management, supply chain logistics, financial risk assessment, or maintenance operations. Furthermore, Timestral offers zero-shot forecasting capabilities and can be tailored to specific domain data through the Mistral Forge. This package is primarily aimed at data scientists, machine learning engineers, and collaborative teams focused on developing robust forecasting solutions; the repository code is licensed under Apache 2.0, while the model weights are governed by a separate Modified MIT license. With its comprehensive features, Timestral is positioned to significantly enhance the accuracy and efficiency of predictive analytics in numerous industries.
API Access
Has API
Yes
API Access
Has API
Yes
Screenshots View All
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Screenshots View All
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Pricing Details
$0
Free and open source under Apache 2.0. Local inference has no subscription, API-key, or per-token charge.
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
Yes
Deployment
Web-Based
No
On-Premises
Yes
iPhone App
Yes
iPad App
Yes
Android App
Yes
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
No
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Tether Data
Country
El Salvador
Website
qvac.tether.io/products/sdk
Vendor Details
Company Name
Mistral AI
Founded
2023
Country
France
Website
github.com/mistralai/timestral
