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
Set `library_name` to `tf-keras`. (#1)
Browse files- Set `library_name` to `tf-keras`. (7705ca234360643e3283b7ac418eebb8382c4d0e)
Co-authored-by: Lucain Pouget <Wauplin@users.noreply.huggingface.co>
README.md
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library_name: keras
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license: creativeml-openrail-m
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- keras
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- diffusers
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- stable-diffusion
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- text-to-image
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library_name: tf-keras
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license: creativeml-openrail-m
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tags:
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- diffusers
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- stable-diffusion
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- text-to-image
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