Text-to-Image
Diffusers
TensorBoard
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use frknayk/dreambooth_training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use frknayk/dreambooth_training with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("frknayk/dreambooth_training", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download diffusers/examples/inference/image_to_image.py from frknayk/dreambooth_training: direct link, hf CLI and curl.
- Browser
- Download file 243 Bytes
-
https://huggingface.co/frknayk/dreambooth_training/resolve/main/diffusers/examples/inference/image_to_image.py
- Command line
-
hf download hf://frknayk/dreambooth_training/diffusers/examples/inference/image_to_image.py
-
curl -L -o image_to_image.py https://huggingface.co/frknayk/dreambooth_training/resolve/main/diffusers/examples/inference/image_to_image.py
243 Bytes
| import warnings | |
| from diffusers import StableDiffusionImg2ImgPipeline # noqa F401 | |
| warnings.warn( | |
| "The `image_to_image.py` script is outdated. Please use directly `from diffusers import" | |
| " StableDiffusionImg2ImgPipeline` instead." | |
| ) | |