deepfake-detector-model-v1 - AI Image Models Tool

Overview

deepfake-detector-model-v1 is an image classification model fine-tuned from google/siglip2-base-patch16-512. It uses the SiglipForImageClassification architecture to label images as either "fake" (deepfakes) or "real". The model is intended for applications such as media authentication, content moderation, forensic analysis, and security. Evaluate performance on representative data before production use.

Key Features

• Classifies images as "fake" or "real".
• Fine-tuned from google/siglip2-base-patch16-512.
• Uses the SiglipForImageClassification architecture.
• Designed for image-based deepfake detection tasks.
• Produces single-label image classification outputs.

Ideal Use Cases

• Media authentication and provenance checks
• Automated content moderation workflows
• Forensic image analysis in investigations
• Security screening and incident review

Getting Started

• Download the model from the Hugging Face model page.
• Load the model using SiglipForImageClassification-compatible code.
• Provide image inputs and run inference to classify "fake" or "real".
• Validate results on representative datasets before deployment.

Pricing

Pricing and licensing not disclosed on the provided model metadata; check the Hugging Face listing for current terms.

Key Information

• Category: Image Models
• Type: AI Image Models Tool