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`.
Browse filesModel 'keras-dreambooth/dreambooth_diffusion_minercraft' seems to be compatible only with "Keras 2" and not "Keras 3". To distinguish them, models compatible with legacy Keras 2.x should be tagged as `tf-keras` while models compatible with Keras 3.x are tagged as `keras`.
This PR updates the model card to replace the explicit `library_name: keras` metadata which is now outdated by `library_name: tf-keras`. Updating this metadata will facilitate its discoverability and usage.
For more information about `keras` and `tf-keras` library names, check out this pull request: https://github.com/huggingface/huggingface.js/pull/774.
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license: creativeml-openrail-m
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library_name: tf-keras
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license: creativeml-openrail-m
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- diffusers
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- text-to-image
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