Update app.py

app.py

@@ -273,7 +273,7 @@ with gr.Blocks(css=".custom-label { font-weight: bold !important; font-size: 16p
     gr.Markdown("<b>☉ Powered by the fine-tuned ViT models that is pre-trained from [FSFM-3C](https://fsfm-3c.github.io/)</b> <br> "
                 "<b>☉ We do not and cannot access or store the data you have uploaded!</b> <br> "
                 "<b>☉ Release (Continuously updating) </b> <br> <b>[V1.0] 2025/02/22-Current🎉</b>: "
-                "1) Updated <b>[✨Unified-detector_v1] for Unified Physical-Digital Face Attack&Forgery Detection, a ViT-B/16-224 (FSFM Pre-trained) detector that could identify Real&Bonafide, Deepfake, Diffduion&AIGC, Spooing&Presentation-attacks facial images or videos </b> ; 2) Provided the selection of the number of video frames (uniformly sampling 1-32 frames, more frames may time-consuming for this page without GPU acceleration); 3) Fixed some errors of V0.1 including loading and prediction. <br>"
+                "1) Updated <b>[✨Unified-detector_v1] for Unified Physical-Digital Face Attack&Forgery Detection, a ViT-B/16-224 (FSFM Pre-trained) detector that could identify Real&Bonafide, Deepfake, Diffusion&AIGC, Spooing&Presentation-attacks facial images or videos </b> ; 2) Provided the selection of the number of video frames (uniformly sampling 1-32 frames, more frames may time-consuming for this page without GPU acceleration); 3) Fixed some errors of V0.1 including loading and prediction. <br>"
                 "<b>[V0.1] 2024/12-2025/02/21</b>: "
                 "Create this page with basic detectors [DfD-Checkpoint_Fine-tuned_on_FF++, FAS-Checkpoint_Fine-tuned_on_MCIO] that follow the paper implementation. <br> ")
     gr.Markdown("- Please <b>provide a facial image or video(<100s)</b>, and <b>select the model</b> for detection: <br> <b>[SUGGEST] [✨Unified-detector_v1_Fine-tuned_on_4_classes]</b> a (FSFM Pre-trained) ViT-B/16-224 for Both Real/Deepfake/Diffusion/Spoofing facial images&videos Detection <br> <b>[DfD-Checkpoint_Fine-tuned_on_FF++]</b> for deepfake detection, FSFM ViT-B/16-224 fine-tuned on the FF++_c23 train&val sets (4 manipulations, 32 frames per video) <br> <b>[FAS-Checkpoint_Fine-tuned_on_MCIO]</b> for face anti-spoofing, FSFM ViT-B/16-224 fine-tuned on the MCIO datasets (2 frames per video)")