Instructions to use obsxrver/Wan2.2_GTA-Style with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use obsxrver/Wan2.2_GTA-Style 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_GTA-Style") prompt = "A man with short gray hair plays a red electric guitar." output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
Wan 2.2 GTA Style
Just a little side project I whipped together for fun. Generates GTA-Style driving videos. I just made it and haven't really experimented all that much yet. But it captures the GTA Aesthetic pretty well. Include gta style in your prompt to activate it.
gta style, a black supercar is driving down the road, speeding past other cars, cyberpunk chinese city, raining, nighttime
gta style, a red sports car is driving quickly on a highway overpass, through a megacity filled with futuristic skyscrapers, overcast, thunderstorming, lightning streaks in distance
My Generation Settings:
LightX2V V1.1 4-step Lora: Strength 0.7
10 Steps
High Noise: 5 steps, Res_Multistep, Simple, Add Noise On, Return Leftover noise On
High Noise: 5 steps, Res_Multistep, Simple, Add noise off, return leftover noise off
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Model tree for obsxrver/Wan2.2_GTA-Style
Base model
Wan-AI/Wan2.2-T2V-A14B