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features
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Description

NVIDIA Nemotron 3.5 Transcribe serves as an open-weight model tailored for developers aiming to create transcription and audio-processing systems. This model transforms audio recordings into text, offering options for both verbatim and edited transcripts, along with features like contextual vocabulary, speaker identification, word-level timestamps, speech translation, language detection, and audio question answering. It boasts a language matrix that encompasses 40 different languages, though the extent of task coverage may vary from one language to another. Capable of processing recordings of up to one hour, the model is optimized for offline inference on compatible NVIDIA GPU hardware and supported runtimes. Developers can seamlessly integrate it into a variety of applications, including speech interfaces, media and meeting processing, customer service analytics, translation software, and other audio comprehension tools. Furthermore, the model's weights, alongside a fine-tuning toolkit, are made available under the OpenMDW-1.1 license, with specific hardware and serving requirements contingent upon the nature of the deployment. This flexibility allows teams to adapt the model for diverse use cases in the field of audio processing and transcription.

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

Screenshots View All

No images available

Integrations

Hugging Face Transformers Yes 
Mistral Forge No 
NVIDIA NIM Yes 
vLLM Yes 

Integrations

Hugging Face Transformers No 
Mistral Forge Yes 
NVIDIA NIM No 
vLLM No 

Pricing Details

The model weights and fine-tuning toolkit are available under the OpenMDW-1.1 license. Hardware and inference-serving costs depend on the selected deployment.
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 No 
iPad App No 
Android App No 
Windows Yes 
Mac No 
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 No 

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

NVIDIA

Founded

1993

Country

United States

Website

research.nvidia.com/labs/nemotron/NVIDIA-Nemotron-3.5-Transcribe/

Vendor Details

Company Name

Mistral AI

Founded

2023

Country

France

Website

github.com/mistralai/timestral

Product Features

Speech Recognition

Audio Capture No 
Automatic Form Fill No 
Automatic Transcription No 
Call Analysis No 
Concatenated Speech No 
Continuous Speech No 
Customizable Macros No 
Multi-Languages No 
Specialty Vocabularies No 
Speech-to-Text Analysis No 
Variable Frequency No 
Voice Recognition No 

Transcription

AI / Machine Learning No 
Annotations No 
Audio/Video File Upload No 
Automatic Transcription No 
Collaboration Tools No 
File Sharing No 
For Manual Transcription No 
Full Text Search No 
Multi-Language Support No 
Natural Language Processing (NLP) No 
Playback Controls No 
Speech Recognition No 
Subtitles No 
Text Editor No 
Timecoding No 

Product Features

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