Instructions to use ms2stationthis/animalcrossingflux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ms2stationthis/animalcrossingflux with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ms2stationthis/animalcrossingflux") prompt = "The image is a digitally rendered screenshot from a video game, likely in the style of a 3D open-world adventure game. The scene is set in a lush, green, grassy area with a river running along the bottom right corner. The \"animalcrossinggc\" aesthetic is clearly visible with the river depicted with a blue hue and reflective surface, indicating a calm water body." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
Nintendo Mentioned
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#1 opened about 1 year ago
by
cockamouse