Instructions to use qiacheng/stable-diffusion-v1-5-lcm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use qiacheng/stable-diffusion-v1-5-lcm with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("qiacheng/stable-diffusion-v1-5-lcm", 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
- Local Apps
- Draw Things
- DiffusionBee
SD1.5 LDM: https://huggingface.co/runwayml/stable-diffusion-v1-5
SD1.5 LCM-Lora: https://huggingface.co/latent-consistency/lcm-lora-sdv1-5
SD1.5 model fused with LCM Lora, saved using diffusers .save_pretrained()
Sample usage:
import torch
from diffusers import StableDiffusionPipeline
pipe = StableDiffusionPipeline.from_pretrained("qiacheng/stable-diffusion-v1-5-lcm")
prompt = "a cat"
height = 512
width = 512
steps = 6
guidance_scale = 1
output = pipe(prompt=prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=guidance_scale, output_type="pil")
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