Text-to-Video
Diffusers
lora
wan
window-seat
travel
surreal
cinematic
contemplative
text-to-image
template:diffusion-lora
Instructions to use artificialguybr/WindowSeat-Redmond-WAN2-T2V-14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use artificialguybr/WindowSeat-Redmond-WAN2-T2V-14B 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", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("artificialguybr/WindowSeat-Redmond-WAN2-T2V-14B") prompt = "Window Seat. A handheld wide shot from inside a moving bus, slightly unsteady, looking through dirty windows at a one-room schoolhouse that sits isolated in the middle of a vast sunflower field in late summer. Through the schoolhouse windows, we glimpse a classroom where adult students—farmers, elderly people, middle-aged workers—sit at tiny children's desks, raising hands to answer questions. A young teacher in vintage clothing writes on a chalkboard. Golden pollen drifts through afternoon air. The sunflowers tower around the building, pressing against windows. Everything glows amber. There's a sense of timelessness, as if education continues outside of time in this forgotten place. Warm 16mm film grain, nostalgic color grading, Malick-inspired naturalism." output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
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