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", torch_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: 1,009 Bytes
69f6fc2 78ed83d 69f6fc2 78ed83d 69f6fc2 78ed83d 69f6fc2 78ed83d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | #!/usr/bin/env python3
from diffusers import StableDiffusionPipeline, DPMSolverSinglestepScheduler, DPMSolverMultistepScheduler, DEISMultistepScheduler, HeunDiscreteScheduler
import time
from huggingface_hub import HfApi
import torch
import sys
path = sys.argv[1]
api = HfApi()
start_time = time.time()
pipe = StableDiffusionPipeline.from_pretrained(path, torch_dtype=torch.float16)
pipe.scheduler = HeunDiscreteScheduler.from_config(pipe.scheduler.config)
pipe = pipe.to("cuda")
prompt = "a highly realistic photo of green turtle"
generator = torch.Generator(device="cuda").manual_seed(0)
image = pipe(prompt, generator=generator, num_inference_steps=25).images[0]
print("Time", time.time() - start_time)
path = "/home/patrick_huggingface_co/images/aa.png"
image.save(path)
api.upload_file(
path_or_fileobj=path,
path_in_repo=path.split("/")[-1],
repo_id="patrickvonplaten/images",
repo_type="dataset",
)
print("https://huggingface.co/datasets/patrickvonplaten/images/blob/main/aa.png")
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