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 ItsJayQz/Valorant_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/ItsJayQz/Valorant_Diffusion/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Yntec/Backups/ItsJayQz/Valorant_Diffusion/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Yntec/Backups/resolve/main/ItsJayQz/Valorant_Diffusion/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 62db169f150808c5c1fa267011c695a4d92c56ab0c0aab1581d2e8bcd32df790
- Size of remote file:
- 492 MB
- SHA256:
- fd95f6550d6bb2af771d15ecd38a4a690618511006bde0a90605ffa539e566dd
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