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
| { | |
| "_class_name": "StableDiffusionPipeline", | |
| "_diffusers_version": "0.14.0", | |
| "feature_extractor": [ | |
| "transformers", | |
| "CLIPFeatureExtractor" | |
| ], | |
| "requires_safety_checker": true, | |
| "safety_checker": [ | |
| "stable_diffusion", | |
| "StableDiffusionSafetyChecker" | |
| ], | |
| "scheduler": [ | |
| "diffusers", | |
| "PNDMScheduler" | |
| ], | |
| "text_encoder": [ | |
| "transformers", | |
| "CLIPTextModel" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "CLIPTokenizer" | |
| ], | |
| "unet": [ | |
| "diffusers", | |
| "UNet2DConditionModel" | |
| ], | |
| "vae": [ | |
| "diffusers", | |
| "AutoencoderKL" | |
| ] | |
| } | |