Text-to-Image
Diffusers
TensorBoard
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use enddl22/dreambooth_tutorial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use enddl22/dreambooth_tutorial with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("enddl22/dreambooth_tutorial", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-500/unet/diffusion_pytorch_model.bin from enddl22/dreambooth_tutorial: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/enddl22/dreambooth_tutorial/resolve/main/checkpoint-500/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://enddl22/dreambooth_tutorial/checkpoint-500/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/enddl22/dreambooth_tutorial/resolve/main/checkpoint-500/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- aa0f70821b0e96356a54eb138e1ab87cf6566a0bd3b5a422a15942144808ed52
- Size of remote file:
- 3.44 GB
- SHA256:
- f94173494e83ff93921b1a1141c37b34eb0bb9fbf28663d6cdd93d01978973e2
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