Instructions to use SidXXD/dog-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/dog-2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SidXXD/dog-2", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download pytorch_custom_diffusion_weights.bin from SidXXD/dog-2: direct link, hf CLI and curl.
- Browser
- Download file 76.7 MB
-
https://huggingface.co/SidXXD/dog-2/resolve/main/pytorch_custom_diffusion_weights.bin
- Command line
-
hf download hf://SidXXD/dog-2/pytorch_custom_diffusion_weights.bin
-
curl -L -o pytorch_custom_diffusion_weights.bin https://huggingface.co/SidXXD/dog-2/resolve/main/pytorch_custom_diffusion_weights.bin
76.7 MB
- Xet hash:
- 64c1df573a7e1f4b994fb6a66111dea7b4295b74f89c1b7d4f66c24477c5ea8b
- Size of remote file:
- 76.7 MB
- SHA256:
- 16547977d948ed3a831bd78b9bb7520d719ef1947d1f7697cf9c1a574aa4a18b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.