Instructions to use keras-dreambooth/dreambooth_diffusion_clay_cups with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use keras-dreambooth/dreambooth_diffusion_clay_cups with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://keras-dreambooth/dreambooth_diffusion_clay_cups") - Diffusers
How to use keras-dreambooth/dreambooth_diffusion_clay_cups 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_clay_cups", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of traditional cups image in bng clay style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f28593031e3f39c1e7c78c235a36db2ada4cc691d44226a4a1abfd8e567a8a2
- Size of remote file:
- 3.44 GB
- SHA256:
- bf76f5d4084c9dca61f9ed6fb0805f2c491a6dc6576b88925e5e2dc71bdb5a67
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