Diffusers
English
stable-diffusion
stable-diffusion-diffusers
inpainting
art
artistic
anime
absolute-realism
Instructions to use diffusers/tools with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers/tools with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers/tools", 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
File size: 658 Bytes
a38f44b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | #!/usr/bin/env python3
from diffusers import AutoPipelineForText2Image, AutoPipelineForImage2Image
import torch
pipe = AutoPipelineForText2Image.from_pretrained("SimianLuo/LCM_Dreamshaper_v7", dtype=torch.float16)
prompt = "A beautiful landscape of a snowy mountain"
num_inference_steps = 1
image = pipe(prompt=prompt, num_inference_steps=num_inference_steps, output_type="pil").images[0]
image.save("snow_mountain.png")
pipe = AutoPipelineForImage2Image.from_pipe(pipe)
prompt = "A beautiful landscape of a very red mountain"
image = pipe(prompt=prompt, image=image, num_inference_steps=10, strength=0.05, output_type="pil").images[0]
image.show()
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