Instructions to use ssdxc/RSTP-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ssdxc/RSTP-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ssdxc/RSTP-lora") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 13f3a3c252e3dafed53c3ba82bf7fef4a0b7fc540c9a63241215e0a8a39564de
- Size of remote file:
- 563 Bytes
- SHA256:
- 5a8ea28b2076d8c819926119a0f0ec1ecfcf41f5ea06eb98fcdb0ecf8e6404aa
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