Instructions to use Lo-Fi-gahara/FlowMatchingModel-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Lo-Fi-gahara/FlowMatchingModel-checkpoints with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Lo-Fi-gahara/FlowMatchingModel-checkpoints", 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
- Xet hash:
- 320e4ec667e3d40e54108f61f0534caf97edae9caad16a7aaf1c344b3f4bd885
- Size of remote file:
- 2.16 GB
- SHA256:
- 2713b49421300ccf787112a261e6aa985683ef01fa6852c09872d35c249331db
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