Instructions to use MirageML/dreambooth-nike with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MirageML/dreambooth-nike 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-nike", 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-nike: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/MirageML/dreambooth-nike/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://MirageML/dreambooth-nike/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/MirageML/dreambooth-nike/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 18f62d0b2ff1b0d62f182e03bc6a518799ad0ac69972278ffa82b165cddb5a0f
- Size of remote file:
- 492 MB
- SHA256:
- b5d74d901fa6a2503a3334d4049fcf7bfbc41f0fad6c53034e2cf05935c2d559
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