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
Upload video/fake-stormer/weights/TopDownDetector_C0_ViTBase224_ST_hm100_tempLOC0.2_4SBI_SAM_mp0.01_temp2_0vidAug_0.25_temp_normlms_IN_model_best.pth with huggingface_hub
Browse files
video/fake-stormer/weights/TopDownDetector_C0_ViTBase224_ST_hm100_tempLOC0.2_4SBI_SAM_mp0.01_temp2_0vidAug_0.25_temp_normlms_IN_model_best.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:3f048719ecff3ffb4d7cb76d29b61057ff4df8f1e8b687075246921215a1e487
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size 989207173
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