Instructions to use Teluv/Wan_Video_Attack_Sprite_Animation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Teluv/Wan_Video_Attack_Sprite_Animation with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Wan-AI/Wan2.2-TI2V-5B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Teluv/Wan_Video_Attack_Sprite_Animation") prompt = "A man with short gray hair plays a red electric guitar." input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png") output = pipe(image=input_image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
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## Model description
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π Model Card: Wan2.2-TI5V-Sprite-Animation-Attack-Lora
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English
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Model Name: Wan2.2-TI5V-Sprite-Animation-Attack-Lora
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## Model description
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π Model Card: Wan2.2-TI5V-Sprite-Animation-Attack-Lora
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π¨ Notice
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This model is currently under R&D and experimental training.
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The file may be unstable, and we plan to provide frequent updates with improved quality as soon as possible.
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Model Name: Wan2.2-TI5V-Sprite-Animation-Attack-Lora
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