--- tags: - Text-to-Video --- ![model example](https://i.imgur.com/3CQlFBR.png) # zeroscope_dark_v2 30x448x256 A watermark-free Modelscope-based video model optimized for producing high-quality 16:9 compositions with varying brightness and a smooth video output. This model was trained using 9,923 clips and 29,769 tagged frames at 30 frames, 448x256 resolution.
zeroscope_v2 30x448x256 is specifically designed for upscaling with [Potat1](https://huggingface.co/camenduru/potat1) using vid2vid in the [1111 text2video](https://github.com/kabachuha/sd-webui-text2video) extension by [kabachuha](https://github.com/kabachuha). Leveraging this model as a preliminary step allows for superior overall compositions at higher resolutions in Potat1, permitting faster exploration in 448x256 before transitioning to a high-resolution render.
### Using it with the 1111 text2video extension 1. Rename the file 'zeroscope_v2_dark_30x448x256.pth' to 'text2video_pytorch_model.pth'. 2. Rename the file 'zeroscope_v2_dark_30x448x256_text.bin' to 'open_clip_pytorch_model.bin'. 3. Replace the respective files in the 'stable-diffusion-webui\models\ModelScope\t2v' directory. ### Upscaling recommendations For upscaling, it's recommended to use Potat1 via vid2vid in the 1111 extension. Aim for a resolution of 1152x640 and a denoise strength between 0.66 and 0.85. Remember to use the same prompt and settings that were used to generate the original clip. ### Known issues Lower resolutions or fewer frames could lead to suboptimal output.
Certain clips might appear with cuts. This will be fixed in the upcoming 2.1 version, which will incorporate a cleaner dataset. Some clips may playback too slowly, requiring prompt engineering for an increased pace.