Instructions to use kerk86/matkovskaya with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kerk86/matkovskaya with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kerk86/matkovskaya", 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 kerk86/matkovskaya: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/kerk86/matkovskaya/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://kerk86/matkovskaya/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kerk86/matkovskaya/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 41e40551761d78df7f7c528fd2b6f6a518f779e1e564043a492a6ed0454ffd70
- Size of remote file:
- 246 MB
- SHA256:
- d59a1e752597e37d881ed5846eb66b566fb1d49f064b8047cc08cd9e938d10b0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.