Instructions to use reallylongaddress/vangoghstyle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use reallylongaddress/vangoghstyle with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("reallylongaddress/vangoghstyle", 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 VanGoghStyle.ckpt from reallylongaddress/vangoghstyle: direct link, hf CLI and curl.
- Browser
- Download file 2.13 GB
-
https://huggingface.co/reallylongaddress/vangoghstyle/resolve/main/VanGoghStyle.ckpt
- Command line
-
hf download hf://reallylongaddress/vangoghstyle/VanGoghStyle.ckpt
-
curl -L -o VanGoghStyle.ckpt https://huggingface.co/reallylongaddress/vangoghstyle/resolve/main/VanGoghStyle.ckpt
2.13 GB
- Xet hash:
- f6f3d55334f607c4c6be53f616a184b14f4b020811d35f32108f2058752a76a9
- Size of remote file:
- 2.13 GB
- SHA256:
- 8dc3f448799b59f49e856652f5669859e12fa227e56bd5a52bd6ce2543b899b8
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