Instructions to use MirageML/dreambooth-adidas with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MirageML/dreambooth-adidas with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MirageML/dreambooth-adidas", 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 MirageML/dreambooth-adidas: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/MirageML/dreambooth-adidas/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://MirageML/dreambooth-adidas/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/MirageML/dreambooth-adidas/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- edebb576b94491c38ff1b5d0d59e94d8824738388d02a8e2ebc52ab909dd2887
- Size of remote file:
- 492 MB
- SHA256:
- 3f55661e53ee412e20cbb581ba2d881f55848c2ff753533a3292effee2f967f3
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