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: 641 Bytes
505afd3 | 1 2 3 4 5 6 7 8 9 | #! /bin/bash
# CUDA_VISIBLE_DEVICES=0,1,2,3 python scripts/train.py --cfg configs/temporal/FakeSFormer_base_c23.yaml
CUDA_VISIBLE_DEVICES=0,1,2,3 python scripts/train.py --cfg configs/temporal/FakeSFormer_base_c0.yaml
# CUDA_VISIBLE_DEVICES=0,1,2,3 python scripts/train.py --cfg configs/temporal/FakeSFormer_base_c40.yaml
# CUDA_VISIBLE_DEVICES=0,1,2,3 python scripts/train.py --cfg configs/temporal/FakeSFormer_large_c23.yaml
# CUDA_VISIBLE_DEVICES=0,1,2,3 python scripts/train.py --cfg configs/temporal/FakeSwin3D_base_c23.yaml
# CUDA_VISIBLE_DEVICES=0,1,2,3 python scripts/train.py --cfg configs/temporal/FakeSFormer_base_c23_224p8.yaml
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