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---
# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
# Doc / guide: https://huggingface.co/docs/hub/model-cards
{}
---
Bf16 safetensors versions of the DynamiCrafter models by Doubiiu: https://huggingface.co/Doubiiu
__________________________________________________________
<!-- Provide a quick summary of what the model is/does. -->

This is a video diffusion model that takes in a single or two still images as a conditioning <br> image and text prompt describing dynamics, and generates looping videos or interpolation from them.

## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->

DynamiCrafter, a (Text-)Image-to-Video/Image Animation approach, aims to generate <br>
short video clips (~2 seconds) from a conditioning image and text prompt.

This model was trained to generate 16 video frames at a resolution of 320x512 <br>
given a context frame of the same resolution.


- **Developed by:** CUHK & Tencent AI Lab
- **Funded by:** CUHK & Tencent AI Lab
- **Model type:** Generative frame interpolation and looping video generation
- **Finetuned from model:** VideoCrafter1 (320x512)

### Model Sources

<!-- Provide the basic links for the model. -->
For research purpose, we recommend our Github repository (https://github.com/Doubiiu/DynamiCrafter), <br>
which includes the detailed implementations.
- **Repository:** https://github.com/Doubiiu/DynamiCrafter
- **Paper:** https://arxiv.org/abs/2310.12190

## Uses

<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->

### Direct Use

<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->

We develop this repository for RESEARCH purposes, so it can only be used for personal/research/non-commercial purposes.



## Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->
- The generated videos are relatively short (2 seconds, FPS=8).
- The model cannot render legible text.
- Faces and people in general may not be generated properly.
- The autoencoding part of the model is lossy, resulting in slight flickering artifacts.



## How to Get Started with the Model

Check out https://github.com/Doubiiu/DynamiCrafter