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

Overview

deepfake-detector-model-v1 is an image classification model fine-tuned from google/siglip2-base-patch16-512 using the SiglipForImageClassification architecture. It classifies images into 'fake' or 'real' and is intended for media authentication, content moderation, forensic analysis, and security workflows.

Key Features

  • Fine-tuned from google/siglip2-base-patch16-512
  • Uses SiglipForImageClassification architecture
  • Binary classification: labels 'fake' or 'real'
  • Intended for media authentication and moderation
  • Image classification model for single-image analysis

Ideal Use Cases

  • Media authentication for newsrooms and publishers
  • Automated content moderation pipelines
  • Forensic analysis of suspected manipulated images
  • Security applications detecting tampered imagery

Getting Started

  • Visit the model page on Hugging Face and download or access model files
  • Install necessary libraries that support SiglipForImageClassification
  • Load the model weights with the SiglipForImageClassification class
  • Preprocess images to the model's input size and format
  • Run inference to receive 'fake' or 'real' predictions
  • Validate outputs against trusted ground truth before deployment

Pricing

Not disclosed on the model page.

Key Information

  • Category: Language Models
  • Type: AI Language Models Tool
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