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# **Deepfake-Quality-Assess-Siglip2**
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**Deepfake-Quality-Assess-Siglip2** is an image classification vision-language encoder model fine-tuned from **google/siglip2-base-patch16-224** for a single-label classification task. It is designed to assess the quality of deepfake images using the **SiglipForImageClassification** architecture.
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The model categorizes images into two classes:
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- **Class 0:** "Issue in Deepfake" – indicating that the deepfake image has noticeable flaws or inconsistencies.
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- **Class 1:** "High-Quality Deepfake" – indicating that the deepfake image is of high quality and appears more realistic.
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# **Run with Transformers**
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```python
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- deepfake
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# **Deepfake-Quality-Assess-Siglip2**
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**Deepfake-Quality-Assess-Siglip2** is an image classification vision-language encoder model fine-tuned from **google/siglip2-base-patch16-224** for a single-label classification task. It is designed to assess the quality of deepfake images using the **SiglipForImageClassification** architecture.
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The model categorizes images into two classes:
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- **Class 0:** "Issue in Deepfake" – indicating that the deepfake image has noticeable flaws or inconsistencies.
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- **Class 1:** "High-Quality Deepfake" – indicating that the deepfake image is of high quality and appears more realistic.
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# **Run with Transformers**
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```python
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