Instructions to use Muapi/sds_particle_flow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/sds_particle_flow with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/sds_particle_flow") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 5679b3b28af57903be3630b4a7cc8999599cab1f58e9ab92b308f51402b7765e
- Size of remote file:
- 387 kB
- SHA256:
- 6234a8228e186c8af84093dc398cb1e30cea142d56906234ce3748b25f38cd40
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