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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 11b5bde68d9306171636a08a5445e433af9cb0575571a369083e0f6905f23854
- Size of remote file:
- 1.36 GB
- SHA256:
- e9c787e9388134c1a25dc69934a51a32a2683b38b8a9b017e1f3a692b8ed6b98
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