sayakpaul / show-1-base

huggingface.co
Total runs: 3
24-hour runs: 0
7-day runs: 0
30-day runs: -2
Model's Last Updated: October 23 2023
text-to-video

Introduction of show-1-base

Model Details of show-1-base

show-1-base

Pixel-based VDMs can generate motion accurately aligned with the textual prompt but typically demand expensive computational costs in terms of time and GPU memory, especially when generating high-resolution videos. Latent-based VDMs are more resource-efficient because they work in a reduced-dimension latent space. But it is challenging for such small latent space (e.g., 64×40 for 256×160 videos) to cover rich yet necessary visual semantic details as described by the textual prompt.

To marry the strength and alleviate the weakness of pixel-based and latent-based VDMs, we introduce Show-1 , an efficient text-to-video model that generates videos of not only decent video-text alignment but also high visual quality.

Model Details

This is the base model of Show-1 that generates videos with 8 keyframes at a resolution of 64x40. The model is finetuned from DeepFloyd/IF-I-L-v1.0 on the WebVid-10M and InternVid dataset.

Usage

Clone the GitHub repository and install the requirements:

git clone https://github.com/showlab/Show-1.git
pip install -r requirements.txt

Run the following command to generate a video from a text prompt. By default, this will automatically download all the model weights from huggingface.

python run_inference.py

You can also download the weights manually and change the pretrained_model_path in run_inference.py to run the inference.

git lfs install

# base
git clone https://huggingface.co/showlab/show-1-base
# interp
git clone https://huggingface.co/showlab/show-1-interpolation
# sr1
git clone https://huggingface.co/showlab/show-1-sr1
# sr2
git clone https://huggingface.co/showlab/show-1-sr2
Citation

If you make use of our work, please cite our paper.

@misc{zhang2023show1,
    title={Show-1: Marrying Pixel and Latent Diffusion Models for Text-to-Video Generation}, 
    author={David Junhao Zhang and Jay Zhangjie Wu and Jia-Wei Liu and Rui Zhao and Lingmin Ran and Yuchao Gu and Difei Gao and Mike Zheng Shou},
    year={2023},
    eprint={2309.15818},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}
Model Card Contact

This model card is maintained by David Junhao Zhang and Jay Zhangjie Wu . For any questions, please feel free to contact us or open an issue in the repository.

Runs of sayakpaul show-1-base on huggingface.co

3
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More Information About show-1-base huggingface.co Model

More show-1-base license Visit here:

https://choosealicense.com/licenses/cc-by-nc-4.0

show-1-base huggingface.co

show-1-base huggingface.co is an AI model on huggingface.co that provides show-1-base's model effect (), which can be used instantly with this sayakpaul show-1-base model. huggingface.co supports a free trial of the show-1-base model, and also provides paid use of the show-1-base. Support call show-1-base model through api, including Node.js, Python, http.

sayakpaul show-1-base online free

show-1-base huggingface.co is an online trial and call api platform, which integrates show-1-base's modeling effects, including api services, and provides a free online trial of show-1-base, you can try show-1-base online for free by clicking the link below.

sayakpaul show-1-base online free url in huggingface.co:

https://huggingface.co/sayakpaul/show-1-base

show-1-base install

show-1-base is an open source model from GitHub that offers a free installation service, and any user can find show-1-base on GitHub to install. At the same time, huggingface.co provides the effect of show-1-base install, users can directly use show-1-base installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

show-1-base install url in huggingface.co:

https://huggingface.co/sayakpaul/show-1-base

Url of show-1-base

show-1-base huggingface.co Url

Provider of show-1-base huggingface.co

sayakpaul
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