Instructions to use obsxrver/wan2.2-t2v-scat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use obsxrver/wan2.2-t2v-scat with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Wan-AI/Wan2.2-T2V-A14B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("obsxrver/wan2.2-t2v-scat") prompt = "A man with short gray hair plays a red electric guitar." output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
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README.md
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# Wan2.2 Scat Lora
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## Info
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All checkpoints (005, 010, 015, ..., 100) are available, so you can experiment to find the best ones.
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IMO use LowNoise 60-75 and HighNoise 85-100 for best results.
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```bash/powershell
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pip install huggingface_hub
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# Wan2.2 Scat Lora
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## Info
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UPDATE: 03-25-2026 New Version: ScatMaster-V2 Released
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```bash/powershell
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pip install huggingface_hub
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