Instructions to use glides/counterfeit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use glides/counterfeit with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("glides/counterfeit", 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
metadata
library_name: diffusers
license: mit
Counterfeit Model Card
Counterfeit V3 is a latent text-to-image diffusion model capable of generating images of people, mainly, and other things, in the style of Japanese anime. For more information about how Stable Diffusion functions, please have a look at 🤗's Stable Diffusion blog.
You can use this with the 🧨Diffusers library from Hugging Face.
Diffusers
from diffusers import StableDiffusionPipeline
import torch
pipeline = StableDiffusionPipeline.from_pretrained("glides/counterfeit").to("cuda")
image = pipeline(prompt="a girl in a white dress").images[0]
image.save("girl.png")
Limitations
- The model does not create perfect illustrations
- The model cannot render legible text
Developed by
- rqdwdw
This model card was written by Noa Roggendorff and is based on the Stable Diffusion v1-5 Model Card.
