Add pipeline tag

README.md

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 license: mit
+pipeline_tag: image-to-video
 language:
 - en
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     <a href="https://arxiv.org/abs/2501.10021">Paper</a> 
 </p>
 
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 This huggingface repo contains the pretrained models of X-Dyna.
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 </p>
 
 
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 ## 📜 Requirements
 * An NVIDIA GPU with CUDA support is required. 
   * We have tested on a single A100 GPU.
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   * **Recommended**: We recommend using a GPU with 80GB of memory.
 * Operating system: Linux
 
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 ## 🧱 Download Pretrained Models
 Due to restrictions we are not able to release the model pretrained with in-house data. Instead, we re-train our model on public datasets, e.g. [HumanVid](https://github.com/zhenzhiwang/HumanVid), and other human video data for research use, e.g.[Pexels](https://www.pexels.com/). We follow the implementation details in our paper and release pretrained weights and other necessary network modules in this huggingface repository. The Stable Diffusion 1.5 UNet can be found [here](https://huggingface.co/stable-diffusion-v1-5/stable-diffusion-v1-5) and place it under pretrained_weights/unet_initialization/SD. After downloading, please put all of them under the pretrained_weights folder. Your file structure should look like this:
 
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 |----...
 ``` 
 
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 ## 🔗 BibTeX
 If you find [X-Dyna](https://arxiv.org/abs/2501.10021) useful for your research and applications, please cite X-Dyna using this BibTeX:
 
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 }
 ```
 
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 ## Acknowledgements
 
-We appreciate the contributions from [AnimateDiff](https://github.com/guoyww/AnimateDiff), [MagicPose](https://github.com/Boese0601/MagicDance), [MimicMotion](https://github.com/tencent/MimicMotion), [Moore-AnimateAnyone](https://github.com/MooreThreads/Moore-AnimateAnyone), [MagicAnimate](https://github.com/magic-research/magic-animate), [IP-Adapter](https://github.com/tencent-ailab/IP-Adapter), [ControlNet](https://arxiv.org/abs/2302.05543), [I2V-Adapter](https://arxiv.org/abs/2312.16693) for their open-sourced research. We appreciate the support from <a href="https://zerg-overmind.github.io/">Quankai Gao</a>, <a href="https://xharlie.github.io/">Qiangeng Xu</a>, <a href="https://ssangx.github.io/">Shen Sang</a>, and <a href="https://tiancheng-zhi.github.io/">Tiancheng Zhi</a> for their suggestions and discussions.
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+We appreciate the contributions from [AnimateDiff](https://github.com/guoyww/AnimateDiff), [MagicPose](https://github.com/Boese0601/MagicDance), [MimicMotion](https://github.com/tencent/MimicMotion), [Moore-AnimateAnyone](https://github.com/MooreThreads/Moore-AnimateAnyone), [MagicAnimate](https://github.com/magic-research/magic-animate), [IP-Adapter](https://github.com/tencent-ailab/IP-Adapter), [ControlNet](https://arxiv.org/abs/2302.05543), [I2V-Adapter](https://arxiv.org/abs/2312.16693) for their open-sourced research. We appreciate the support from <a href="https://zerg-overmind.github.io/">Quankai Gao</a>, <a href="https://xharlie.github.io/">Qiangeng Xu</a>, <a href="https://ssangx.github.io/">Shen Sang</a>, and <a href="https://tiancheng-zhi.github.io/">Tiancheng Zhi</a> for their suggestions and discussions.