Instructions to use Remade-AI/Fire with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Remade-AI/Fire 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/Wan2.1-T2V-14B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Remade-AI/Fire") prompt = "A lone tree stands silhouetted against the backdrop of a wildfire consuming a vast forest, the sky filled with smoke." output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- Xet hash:
- 16d6ec39a5950098b800612a2fce001b85157e871b72cfb2ca0816f6ec1ee7c6
- Size of remote file:
- 1.7 MB
- SHA256:
- d3241710ccd64cbdca1ccae52b7918d80b0cf80dd1e16efd71ae0a7459cc933b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.