--- license: creativeml-openrail-m library_name: diffusers inference: true pipeline_tag: text-to-video tags: - text-to-video - text-to-image language: - ar metrics: - accuracy --- # Text2Video-Zero Model Card - ControlNet Canny Aracane Style [Text2Video-Zero](https://arxiv.org/abs/2303.13439) is a zero-shot text to video generator. It can perform `zero-shot text-to-video generation`, `Video Instruct Pix2Pix` (instruction-guided video editing), `text and pose conditional video generation`, `text and canny-edge conditional video generation`, and `text, canny-edge and dreambooth conditional video generation`. For more information about this work, please have a look at our [paper](https://arxiv.org/abs/2303.13439) and our demo: [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PAIR/Text2Video-Zero) Our [code](https://github.com/Picsart-AI-Research/Text2Video-Zero) works with any StableDiffusion base model. This model provides [DreamBooth](https://arxiv.org/abs/2208.12242) weights for the `Arcane style` to be used with edge guidance (using [ControlNet](https://arxiv.org/abs/2302.05543)) in text2video zero. ## Weights for Text2Video-Zero We converted the original weights into diffusers and made them usable for [ControlNet](https://arxiv.org/abs/2302.05543) with edge guidance using: https://github.com/lllyasviel/ControlNet/discussions/12. ### Model Details - **Developed by:** Levon Khachatryan, Andranik Movsisyan, Vahram Tadevosyan, Roberto Henschel, Zhangyang Wang, Shant Navasardyan and Humphrey Shi - **Model type:** Dreambooth text-to-image and text-to-video generation model with edge control for text2video zero - **Language(s):** English - **License:** [The CreativeML OpenRAIL M license](https://huggingface.co/spaces/CompVis/stable-diffusion-license). - **Model Description:** This is a model for [text2video zero](https://github.com/Picsart-AI-Research/Text2Video-Zero) with edge guidance and arcane style. It can be used also with ControlNet in a text-to-image setup with edge guidance. - **DreamBoth Keyword:** arcane style - **Resources for more information:** [GitHub](https://github.com/Picsart-AI-Research/Text2Video-Zero), [Paper](https://arxiv.org/abs/2303.13439), [CIVITAI](https://civitai.com/models/23/arcane-diffusion). - **Cite as:** @article{text2video-zero, title={Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators}, author={Khachatryan, Levon and Movsisyan, Andranik and Tadevosyan, Vahram and Henschel, Roberto and Wang, Zhangyang and Navasardyan, Shant and Shi, Humphrey}, journal={arXiv preprint arXiv:2303.13439}, year={2023} } ## Original Weights The Dreambooth weights for the Arcane style were taken from [CIVITAI](https://civitai.com/models/23/arcane-diffusion). ### Model Details - **Developed by:** Quiet_Joker (Username listed on CIVITAI) - **Model type:** Dreambooth text-to-image generation model - **Language(s):** English - **License:** [The CreativeML OpenRAIL M license](https://huggingface.co/spaces/CompVis/stable-diffusion-license). - **Model Description:** This is a model that was created using [DreamBooth](https://arxiv.org/abs/2208.12242) to generate images with Arcane style, based on text prompts. - **DreamBoth Keyword:** arcane style - **Resources for more information:** [CIVITAI](https://civitai.com/models/23/arcane-diffusion). ## Biases content acknowledgement: Beware that Text2Video-Zero may output content that reinforces or exacerbates societal biases, as well as realistic faces, pornography, and violence. Text2Video-Zero in this demo is meant only for research purposes. # Citation @article{text2video-zero, title={Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators}, author={Khachatryan, Levon and Movsisyan, Andranik and Tadevosyan, Vahram and Henschel, Roberto and Wang, Zhangyang and Navasardyan, Shant and Shi, Humphrey}, journal={arXiv preprint arXiv:2303.13439}, year={2023} }