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:
- e68886a73a51b3b5b687526ad10b3497e8ab0e338e72fb4dc7a07e4ed46ca1e5
- Size of remote file:
- 2.16 GB
- SHA256:
- d61d5caf61538889859fe8c16ea61a59144a8ac7fcff531a0177d7cea252b57e
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