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 video/fake-stormer/model_code/configs/get_config.py from deepsafe/deepsafe-services: direct link, hf CLI and curl.
- Browser
- Download file 348 Bytes
-
https://huggingface.co/deepsafe/deepsafe-services/resolve/3680c22ed9fca1657ae7b4c5c4f89042446aa503/video/fake-stormer/model_code/configs/get_config.py
- Command line
-
hf download hf://deepsafe/deepsafe-services@3680c22ed9fca1657ae7b4c5c4f89042446aa503/video/fake-stormer/model_code/configs/get_config.py
-
curl -L -o get_config.py https://huggingface.co/deepsafe/deepsafe-services/resolve/3680c22ed9fca1657ae7b4c5c4f89042446aa503/video/fake-stormer/model_code/configs/get_config.py
348 Bytes
| # -*- coding: utf-8 -*- | |
| import os | |
| from yaml import dump, load | |
| try: | |
| from yaml import CDumper as Dumper | |
| from yaml import CLoader as Loader | |
| except ImportError: | |
| from yaml import Loader, Dumper | |
| from box import Box as edict | |
| def load_config(cfg): | |
| with open(cfg) as f: | |
| config = load(f, Loader=Loader) | |
| return edict(config) | |