Text-to-Image
Diffusers
Safetensors
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
Instructions to use hippoleveque/retfutbrr-style-sd-v14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hippoleveque/retfutbrr-style-sd-v14 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hippoleveque/retfutbrr-style-sd-v14", dtype=torch.bfloat16, device_map="cuda") prompt = "an illustration of a tree in retfutbrr style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
DreamBooth model for the retfutbrr concept trained by hippoleveque on the hippoleveque/retrofuturistic-images dataset.
This is a Stable Diffusion model fine-tuned on the retfutbrr concept with DreamBooth. It can be used by modifying the instance_prompt: an illustration of retfutbrr style
Description
This is a Stable Diffusion v1.4 model fine-tuned on retfutbrr style
Usage
from diffusers import StableDiffusionPipeline
pipeline = StableDiffusionPipeline.from_pretrained('hippoleveque/retfutbrr-style-sd-v14')
image = pipeline().images[0]
image
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