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
File size: 294 Bytes
505afd3 | 1 2 3 4 5 6 | #! /bin/bash
# CUDA_VISIBLE_DEVICES=0,1,2,3 python scripts/train.py --cfg configs/spatial/swin_sbi_base.yaml
CUDA_VISIBLE_DEVICES=0 python scripts/train.py --cfg configs/spatial/swin_bi_small.yaml
# CUDA_VISIBLE_DEVICES=0,1,2,3 python scripts/train.py --cfg configs/spatial/swin_sbi_tiny.yaml
|