Text-to-Video
Diffusers
Safetensors
video-generation
game-rendering
game-editing
diffusion
g-buffer
relighting
wan2.1
Instructions to use Brian9999/game-editing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Brian9999/game-editing with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Brian9999/game-editing", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Improve model card: add pipeline tag, paper/code links, and sample usage
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the Hugging Face community science team. I've updated the model card for the Game Editing model to make it more informative and discoverable:
- Updated the
pipeline_tagtoimage-to-video(as the model is G-buffer guided). - Added links to the Generative World Renderer paper, the Project Page, and the official GitHub repository.
- Included a "Sample Usage" section with the CLI command found in your documentation.
- Added the BibTeX citation for researchers to easily cite your work.