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deepfake-image-detection

deepfake-image-detection

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Associated Products
Features
Description
Hive’s Deepfake Image Detection model analyzes images and returns a confidence score on how likely the image contains a deepfake.
Publisher
Hive
Latest Tag
latest
Modified
May 17, 2025
Compressed Size
12.98 GB
Multinode Support
No
Multi-Arch Support
Yes
latest (Latest) Security Scan Results

Linux / amd64

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What Is NVIDIA NIM?

NVIDIA NIM, part of NVIDIA AI Enterprise, is a set of easy-to-use microservices designed to speed up generative AI deployment in enterprises. Supporting a wide range of AI models, including NVIDIA AI foundation and custom models, it ensures seamless, scalable AI inferencing, on-premises or in the cloud, leveraging industry standard APIs.

Hive’s Deepfake Image Detection model analyzes images and returns a confidence score on how likely the image contains a deepfake. The model was trained on millions of images from dozens of major deepfake generators, and has frequent updates to account for new deepfake engines and adversarial techniques.

NVIDIA NIM offers prebuilt containers for multimodal safety models that can be used to safeguard AI applications — or any application that needs to understand and generate multimodal content. Each NIM consists of a container and a model and uses a CUDA-accelerated runtime for all NVIDIA GPUs, with special optimizations available for many configurations. Whether on-premises or in the cloud, NIM is the fastest way to achieve accelerated generative AI inference at scale.

High Performance Features

NVIDIA NIM abstracts away model inference internals such as execution engine and runtime operations.

  • Scalable Deployment: NVIDIA NIM is performant and can easily and seamlessly scale from a few users to millions.
  • Flexible Integration: Easily incorporate the microservice into existing workflows and applications.
  • Enterprise-Grade Security: Data privacy is paramount. NVIDIA NIM emphasizes security by using safetensors, constantly monitoring and patching CVEs in our stack and conducting internal penetration tests.

Applications

Consumer applications: Detect deepfake images often used by fraudsters and bad actors Social Media Monitoring: Screen for scams posted on social media leveraging deepfake content of celebrities and public figures Identity Verification: Confirm photo verification documents provided by users are legitimate and not deepfaked

Getting started with NVIDIA NIM

Deploying and integrating NVIDIA NIM is straightforward thanks to our industry standard APIs. Visit the NIM for Multimodal Safety page for release documentation, deployment guides and more.

Security Vulnerabilities in Open Source Packages

Please review the Security Scanning tab to view the latest security scan results.

For certain open-source vulnerabilities listed in the scan results, NVIDIA provides a response in the form of a Vulnerability Exploitability eXchange (VEX) document. The VEX information can be reviewed and downloaded from the Security Scanning tab.

Get Help

Enterprise Support

Get access to knowledge base articles and support cases or submit a ticket.

NVIDIA NIM Documentation

Visit the NIM for Multimodal Safety page for release documentation, deployment guides and more.

Governing Terms

The NIM container is governed by the NVIDIA AI Product Agreement; and the use of this model is governed by the Hive Model Agreement.

You are responsible for ensuring that your use of NVIDIA AI Foundation Models complies with all applicable laws.