Instructions to use latent-consistency/lcm-lora-ssd-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use latent-consistency/lcm-lora-ssd-1b with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("segmind/SSD-1B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("latent-consistency/lcm-lora-ssd-1b") 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:
- 2332aba8b0cb35f8d3e9c476dad238598c469647de8c1d602392c9c51a76e3a7
- Size of remote file:
- 1.66 MB
- SHA256:
- 05ef31ad1eb990fcfd50458192a8a3ecb931607998fd2ff6326b4e125514a812
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