Instructions to use AMAN-B/Demo-Dreambooth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AMAN-B/Demo-Dreambooth with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AMAN-B/Demo-Dreambooth", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from AMAN-B/Demo-Dreambooth: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/AMAN-B/Demo-Dreambooth/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://AMAN-B/Demo-Dreambooth/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AMAN-B/Demo-Dreambooth/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- aa0ef57c42990f260ca8f6c668d59450e089f516519a2d3ef9d263636e557398
- Size of remote file:
- 492 MB
- SHA256:
- 37d7de00b98ceb44f3668e4f5015c7697a77fdc2183c8667f9c754cc7ac04158
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