Instructions to use keras-dreambooth/dreambooth_diffusion_akitainu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use keras-dreambooth/dreambooth_diffusion_akitainu with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy), and from_pretrained_keras was removed in huggingface_hub 1.0. # See https://github.com/keras-team/tf-keras for more details. # !pip install "huggingface_hub<1.0" tf_keras from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("keras-dreambooth/dreambooth_diffusion_akitainu") - Diffusers
How to use keras-dreambooth/dreambooth_diffusion_akitainu with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("keras-dreambooth/dreambooth_diffusion_akitainu", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of akt## dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Commit History
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Set `library_name` to `tf-keras`. (#1)
Verified signature- Set `library_name` to `tf-keras`. (003404fa7bcf1bd0661b6b60a1f939083a64a7dd) Co-authored-by: Lucain Pouget <Wauplin@users.noreply.huggingface.co>52fda18
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