Instructions to use deepsafe/deepsafe-services with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use deepsafe/deepsafe-services with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("deepsafe/deepsafe-services", 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 image/fsd/weights/fsd_transforms.pt from deepsafe/deepsafe-services: direct link, hf CLI and curl.
- Browser
- Download file 42.2 MB
-
https://huggingface.co/deepsafe/deepsafe-services/resolve/main/image/fsd/weights/fsd_transforms.pt
- Command line
-
hf download hf://deepsafe/deepsafe-services/image/fsd/weights/fsd_transforms.pt
-
curl -L -o fsd_transforms.pt https://huggingface.co/deepsafe/deepsafe-services/resolve/main/image/fsd/weights/fsd_transforms.pt
42.2 MB
- Xet hash:
- e7b1c258ccb93b61a42be4e132b7de32d0920bfb2f9908b235ae1687e407f47c
- Size of remote file:
- 42.2 MB
- SHA256:
- 1e87d792b413101e58d9de71551182a1fab8b879ca6f6ba9780b6adcb9a5a699
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.