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--- |
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license: creativeml-openrail-m |
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base_model: nitrosocke/mo-di-diffusion |
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training_prompt: A bear is playing guitar. |
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tags: |
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- tune-a-video |
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- text-to-video |
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- diffusers |
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inference: false |
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--- |
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# Tune-A-Video - Modern Disney |
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## Model Description |
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- Base model: [nitrosocke/mo-di-diffusion](https://huggingface.co/nitrosocke/mo-di-diffusion) |
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- Training prompt: a bear is playing guitar. |
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## Samples |
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Test prompt: a [handsome prince/magical princess/rabbit/baby] is playing guitar, modern disney style. |
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## Usage |
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Clone the github repo |
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```bash |
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git clone https://github.com/showlab/Tune-A-Video.git |
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``` |
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Run inference code |
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```python |
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from tuneavideo.pipelines.pipeline_tuneavideo import TuneAVideoPipeline |
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from tuneavideo.models.unet import UNet3DConditionModel |
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from tuneavideo.util import save_videos_grid |
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import torch |
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pretrained_model_path = "nitrosocke/mo-di-diffusion" |
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unet_model_path = "Tune-A-Video-library/mo-di-bear-guitar" |
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unet = UNet3DConditionModel.from_pretrained(unet_model_path, subfolder='unet', torch_dtype=torch.float16).to('cuda') |
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pipe = TuneAVideoPipeline.from_pretrained(pretrained_model_path, unet=unet, torch_dtype=torch.float16).to("cuda") |
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pipe.enable_xformers_memory_efficient_attention() |
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prompt = "a magical princess is playing guitar, modern disney style" |
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video = pipe(prompt, video_length=8, height=512, width=512, num_inference_steps=50, guidance_scale=7.5).videos |
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save_videos_grid(video, f"./{prompt}.gif") |
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``` |
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## Related Papers: |
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- [Tune-A-Video](https://arxiv.org/abs/2212.11565): One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation |
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- [Stable Diffusion](https://arxiv.org/abs/2112.10752): High-Resolution Image Synthesis with Latent Diffusion Models |
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