Instructions to use WALIDALI/marimwly with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WALIDALI/marimwly with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WALIDALI/marimwly", 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
- Xet hash:
- 7d63f9c13dc952c608de07a9f3840c1f2e1803352fe7b66d5adcd51d4fcb3b7d
- Size of remote file:
- 246 MB
- SHA256:
- 5aca0e94f2ab4d0c5c9f6f8e2231fb99c78286ee3797f55585ef5cb1ddbfa947
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