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
Download audio/safeear/weights/model.ckpt from deepsafe/deepsafe-services: direct link, hf CLI and curl.
- Browser
- Download file 762 MB
-
https://huggingface.co/deepsafe/deepsafe-services/resolve/main/audio/safeear/weights/model.ckpt
- Command line
-
hf download hf://deepsafe/deepsafe-services/audio/safeear/weights/model.ckpt
-
curl -L -o model.ckpt https://huggingface.co/deepsafe/deepsafe-services/resolve/main/audio/safeear/weights/model.ckpt
762 MB
- Xet hash:
- c20d3ced4163d72897bcaa3803aacd5f3ed0fb5a8f6a2404dbd5dc4666e6e75b
- Size of remote file:
- 762 MB
- SHA256:
- 6e907978cad9a742fa0b410d653cc72855cccd75eac610e67b2da6a41a944993
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