Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
wildcard
Instructions to use Someman/bird-danphe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Someman/bird-danphe with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Someman/bird-danphe", dtype=torch.bfloat16, device_map="cuda") prompt = "a big dog with danphe face" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
metadata
license: creativeml-openrail-m
tags:
- pytorch
- diffusers
- stable-diffusion
- text-to-image
- diffusion-models-class
- dreambooth-hackathon
- wildcard
widget:
- text: a big dog with danphe face
DreamBooth model for the bird concept trained by Someman on the Someman/danphe dataset.
This is a Stable Diffusion model fine-tuned on the bird concept with DreamBooth. It can be used by modifying the instance_prompt: a photo of bird danphe
This model was created as part of the DreamBooth Hackathon 🔥. Visit the organisation page for instructions on how to take part!
Description
This is a Stable Diffusion model fine-tuned on danphe images for the wildcard theme.
Usage
from diffusers import StableDiffusionPipeline
pipeline = StableDiffusionPipeline.from_pretrained('Someman/bird-danphe')
image = pipeline().images[0]
image