Instructions to use keras-dreambooth/dreambooth_diffusion_minercraft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use keras-dreambooth/dreambooth_diffusion_minercraft with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy) # See https://github.com/keras-team/tf-keras for more details. from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("keras-dreambooth/dreambooth_diffusion_minercraft") - Diffusers
How to use keras-dreambooth/dreambooth_diffusion_minercraft 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_minercraft", dtype=torch.bfloat16, device_map="cuda") prompt = "a fishing village under a cherry blossom forest at sunset in mrf style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- f7601799f0b41cafc9486735e91d75dc6321d77390fce9cf45c47f772389de2d
- Size of remote file:
- 1.93 MB
- SHA256:
- d0386e0bd804e16eb2d347dfac2a66ebf30eba7bb32074b21c2e059551590bd9
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