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
Add model card explaining what these weights are and where they came from
Browse files
README.md
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---
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license: other
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license_name: mixed-upstream
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license_link: https://github.com/deepsafehq/deepsafe-bench/blob/main/THIRD_PARTY_NOTICES.md
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tags:
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- deepfake-detection
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- model-zoo
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- mirror
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---
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# DeepSafe Model Weights
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Weights for the 24 models used by
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[DeepSafe](https://github.com/deepsafehq/deepsafe-bench), a benchmark that
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tests how well deepfake detectors actually work.
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**These weights are not ours.** Each belongs to the authors of the model it
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came from and keeps that model's own license. See
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[THIRD_PARTY_NOTICES.md](https://github.com/deepsafehq/deepsafe-bench/blob/main/THIRD_PARTY_NOTICES.md).
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## Why mirror them
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Paper download links rot. DeepSafe lost one model outright when its weights
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were deleted from the host its paper pointed at. Mirroring means setup still
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works in three years.
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## Usage
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You do not normally download this by hand. `setup.sh` does it:
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```bash
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git clone https://github.com/deepsafehq/deepsafe-bench.git
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cd deepsafe-bench && bash setup.sh
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```
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Roughly 44 GB, covering 7 image, 9 video, 3 audio and 5 provenance models,
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plus the CLIP and face-detection caches they depend on. No token needed.
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Model *code* is mirrored separately at
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[deepsafe/model-code](https://huggingface.co/deepsafe/model-code).
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## Takedown
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If you authored any of these weights and want them removed, open an issue at
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https://github.com/deepsafehq/deepsafe-bench and they come down within 48
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hours, no questions asked.
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