Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
stable-diffusion
stable-diffusion-1.5
Mixture of Experts
segmoe
Instructions to use RachidAR/AFlow-SegMoe-1Bx3-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RachidAR/AFlow-SegMoe-1Bx3-v0.1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("RachidAR/AFlow-SegMoe-1Bx3-v0.1", 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 Settings
- Draw Things
- DiffusionBee
Warning
This is an experimental model. It works only with segmoe library!
Experts
- source_model: Lykon/dreamshaper-8 (base)
- source_model: Lykon/AAM_AnyLora_AnimeMix
- source_model: stablediffusionapi/realistic-vision-51
Usage
This model can be used via the segmoe library.
Make sure to install segmoe by running
pip install segmoe
from segmoe import SegMoEPipeline
pipeline = SegMoEPipeline("RachidAR/AFlow-SegMoe-1Bx3-v0.1", device = "cuda", safety_checker = None)
prompt = "cosmic canvas, orange city background, painting of a chubby cat"
negative_prompt = "nsfw, bad quality, worse quality"
img = pipeline(
prompt=prompt,
negative_prompt=negative_prompt,
height=1024,
width=1024,
num_inference_steps=25,
guidance_scale=7.5,
).images[0]
img.save("image.png")
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