Instructions to use BirdL/FancyVideo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BirdL/FancyVideo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BirdL/FancyVideo", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -5,6 +5,8 @@ pipeline_tag: text-to-video
|
|
| 5 |
Unoffical mirror of FancyVideo, requires SD-V1.5 or another other base model to be required seperately.
|
| 6 |
Inference and training code is located at https://github.com/360CVGroup/FancyVideo
|
| 7 |
|
|
|
|
|
|
|
| 8 |
@misc{feng2024fancyvideodynamicconsistentvideo,
|
| 9 |
title={FancyVideo: Towards Dynamic and Consistent Video Generation via Cross-frame Textual Guidance},
|
| 10 |
author={Jiasong Feng and Ao Ma and Jing Wang and Bo Cheng and Xiaodan Liang and Dawei Leng and Yuhui Yin},
|
|
|
|
| 5 |
Unoffical mirror of FancyVideo, requires SD-V1.5 or another other base model to be required seperately.
|
| 6 |
Inference and training code is located at https://github.com/360CVGroup/FancyVideo
|
| 7 |
|
| 8 |
+
8/20/24: An offical repo has been created at huggingface.co/qihoo360/FancyVideo
|
| 9 |
+
|
| 10 |
@misc{feng2024fancyvideodynamicconsistentvideo,
|
| 11 |
title={FancyVideo: Towards Dynamic and Consistent Video Generation via Cross-frame Textual Guidance},
|
| 12 |
author={Jiasong Feng and Ao Ma and Jing Wang and Bo Cheng and Xiaodan Liang and Dawei Leng and Yuhui Yin},
|