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
sync from GitHub (e4aeaa8)
Browse files- video/pwtf-dvd/app.py +1 -1
video/pwtf-dvd/app.py
CHANGED
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@@ -141,9 +141,9 @@ def _load_models() -> None:
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from model.framework import get_model
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from test_tools.common import detect_all, grab_all_frames
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from test_tools.utils import get_crop_box
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from test_tools.ct.operations import find_longest, multiple_tracking
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from test_tools.faster_crop_align_xray import FasterCropAlignXRay
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_detect_all = detect_all
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_grab_all_frames = grab_all_frames
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from model.framework import get_model
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from test_tools.common import detect_all, grab_all_frames
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from test_tools.ct.operations import find_longest, multiple_tracking
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from test_tools.faster_crop_align_xray import FasterCropAlignXRay
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from test_tools.utils import get_crop_box
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_detect_all = detect_all
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_grab_all_frames = grab_all_frames
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