Vox-adv-cpk.pth.tar - File Download

Here’s a content package you can use for a webpage, documentation, or README file to facilitate the download of the vox-adv-cpk.pth.tar file. Download: vox-adv-cpk.pth.tar File Description vox-adv-cpk.pth.tar is a pre-trained model checkpoint file (PyTorch format) commonly used for adversarial generation tasks on VoxCeleb datasets , particularly in face reenactment , audio-driven talking head generation , or adversarial latent manipulation projects (e.g., first-order motion models, face vid2vid, or GAN-based facial animation).

## Option 3: Direct HTML Link Block (for a website) vox-adv-cpk.pth.tar file download

```html <section class="download-box"> <h3>vox-adv-cpk.pth.tar</h3> <p><strong>Size:</strong> ~350 MB</p> <p><strong>Type:</strong> PyTorch model checkpoint</p> <a href="https://your-server.com/path/vox-adv-cpk.pth.tar" class="download-button" download>⬇️ Download File</a> <p class="note">If the link is broken, check the <a href="/models">model archive</a>.</p> </section> </code></pre> <hr> <h2>Important Notes for Your Users</h2> <ul> <li><strong>Copyright & License:</strong> This file may be under a non-commercial license (e.g., CC BY-NC 4.0). Ensure compliance with the original model’s license.</li> <li><strong>File Integrity:</strong> After download, verify with <code>md5sum</code> or <code>sha256sum</code> if hashes are provided by the source.</li> <li><strong>Alternative:</strong> If the download is missing, check the project’s GitHub Issues or contact the model author.</li> </ul> <hr> Here’s a content package you can use for

(Replace with actual working URLs from the project you are referencing.) # Example: Download via wget wget https://path-to-your-file/vox-adv-cpk.pth.tar Move to checkpoint directory mv vox-adv-cpk.pth.tar checkpoints/ Ensure compliance with the original model’s license

gdown https://drive.google.com/uc?id=YOUR_FILE_ID </code></pre> <p><strong>Expected SHA256:</strong> <code>5f3a8b...</code> (check after download)</p> <p>Place it in <code>./checkpoints/</code> before running <code>demo.py</code>.</p> <pre><code> ---

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