Instructions to use Falah/fighter-style with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Falah/fighter-style with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Falah/fighter-style", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Download unet/diffusion_pytorch_model.bin from Falah/fighter-style: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/Falah/fighter-style/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Falah/fighter-style/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Falah/fighter-style/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 50f4817952ef0a84bd731d2728ab20008b0e73c792d51ac520e070b1e0e4d35c
- Size of remote file:
- 3.44 GB
- SHA256:
- 377f8fa60ab8c469bc8d5720116e82a2e1af84af2ed092893bbfd2c8447518ef
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