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:
- 005112fd9c1e2cda89fc0c1889034a4f9ce38854473237f34c28ddd393635e37
- Size of remote file:
- 56 Bytes
- SHA256:
- 9654f8206fc3eabd712a32e58cb06b17447f52746832711b75844f7231a7d626
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