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:
- 162629d34edf63dbe813cf5eb1946c91afb42364d607b96d2fca5a0a87cc8838
- Size of remote file:
- 2.16 GB
- SHA256:
- 2d2755eca22d177dfb411810b9f293858f773c79ab93b638daaf89e43a1acebd
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