Text-to-Image
Diffusers
Keras
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
keras-sprint
keras-dreambooth
scifi
Instructions to use nielsgl/dreambooth-bored-ape with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nielsgl/dreambooth-bored-ape with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nielsgl/dreambooth-bored-ape", dtype=torch.bfloat16, device_map="cuda") prompt = "a drawing of drawbayc monkey as a turtle" image = pipe(prompt).images[0] - Keras
How to use nielsgl/dreambooth-bored-ape with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://nielsgl/dreambooth-bored-ape") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- dfaf4e2e31bf1af677e1e31a159ba50b78737902ca2ab5729ccdd15a11e69200
- Size of remote file:
- 335 MB
- SHA256:
- a4302e1efa25f3a47ceb7536bc335715ad9d1f203e90c2d25507600d74006e89
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