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 provenance/audioseal/requirements.txt from deepsafe/deepsafe-services: direct link, hf CLI and curl.
- Browser
- Download file 134 Bytes
-
https://huggingface.co/deepsafe/deepsafe-services/resolve/3680c22ed9fca1657ae7b4c5c4f89042446aa503/provenance/audioseal/requirements.txt
- Command line
-
hf download hf://deepsafe/deepsafe-services@3680c22ed9fca1657ae7b4c5c4f89042446aa503/provenance/audioseal/requirements.txt
-
curl -L -o requirements.txt https://huggingface.co/deepsafe/deepsafe-services/resolve/3680c22ed9fca1657ae7b4c5c4f89042446aa503/provenance/audioseal/requirements.txt
134 Bytes
| fastapi==0.115.12 | |
| uvicorn==0.34.2 | |
| pydantic==2.11.1 | |
| audioseal==0.1.4 | |
| torch>=2.0.0 | |
| torchaudio>=2.0.0 | |
| numpy>=1.24,<2.0 | |
| soundfile>=0.12.0 | |