This is a LoRA model finetuned on Wan-I2V-14B-480P. It turns things in the image into fluffy toys. 🌟 Give it a star if you like it.
🎞️ Showcases
🐍 Installation
# Python 3.12 and PyTorch 2.6.0 are tested.
pip install torch==2.6.0 torchvision==0.21.0 --index-url https://download.pytorch.org/whl/cu124
pip install -r requirements.txt
🔄 Inference
python generate.py --prompt "The video opens with a clear view of a $name. Then it transforms to a b6e9636 JellyCat-style $name. It has a face and a cute, fluffy and playful appearance." --image $image_path --save_file "output.mp4" --offload_type leaf_level
Note:
Change $name to the object name you want to transform.
$image_path is the path to the first frame image.
Choose --offload_type from [‘leaf_level’, ‘block_level’, ‘none’, ‘model’]. More details can be found here.
VRAM usage and generation time of different --offload_type are listed below.
--offload_type
VRAM Usage
Generation Time (NVIDIA A100)
leaf_level
11.9 GB
17m17s
block_level (num_blocks_per_group=1)
20.5 GB
16m48s
model
39.4 GB
16m24s
none
55.9 GB
16m08s
🤝 Acknowledgements
Special thanks to these projects for their contributions to the community!
Alibaba Research Intelligence Computing
This is a LoRA model finetuned on Wan-I2V-14B-480P. It turns things in the image into fluffy toys. 🌟 Give it a star if you like it.
🎞️ Showcases
🐍 Installation
🔄 Inference
Note:
Change
$nameto the object name you want to transform.$image_pathis the path to the first frame image.Choose
--offload_typefrom [‘leaf_level’, ‘block_level’, ‘none’, ‘model’]. More details can be found here.VRAM usage and generation time of different
--offload_typeare listed below.--offload_type🤝 Acknowledgements
Special thanks to these projects for their contributions to the community!
📄 Our previous work