Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
wildcard
Instructions to use Ducco/dota-style with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Ducco/dota-style with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Ducco/dota-style", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of an elephant in dota style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download vae/diffusion_pytorch_model.bin from Ducco/dota-style: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/Ducco/dota-style/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Ducco/dota-style/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Ducco/dota-style/resolve/main/vae/diffusion_pytorch_model.bin
167 MB
- Xet hash:
- 9fbb526d6483a977b7631106c4e3e101d2947f46dc9c9c8e6cd83b4424c482ce
- Size of remote file:
- 167 MB
- SHA256:
- 11bc15ceb385823b4adb68bd5bdd7568d0c706c3de5ea9ebcb0b807092fc9030
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