Instructions to use Yntec/Backups with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/Backups with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Yntec/Backups", 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
Download wavymulder/collage-diffusion/text_encoder/pytorch_model.bin from Yntec/Backups: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/Yntec/Backups/resolve/main/wavymulder/collage-diffusion/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Yntec/Backups/wavymulder/collage-diffusion/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Yntec/Backups/resolve/main/wavymulder/collage-diffusion/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 81d9cefcd9dd04252cb07bb9199d3e84c572aec9b602569cccbbaf4cec56d801
- Size of remote file:
- 492 MB
- SHA256:
- 64fa8fd2c2630e55ca47bec6c5f6be693f0c2faaadcc10d87debc62b0a10b109
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.