Instructions to use Bl4ckSpaces/z-image-turbo-pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Bl4ckSpaces/z-image-turbo-pipeline with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Bl4ckSpaces/z-image-turbo-pipeline", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder_2/model.safetensors from Bl4ckSpaces/z-image-turbo-pipeline: direct link, hf CLI and curl.
- Browser
- Download file 2.82 GB
-
https://huggingface.co/Bl4ckSpaces/z-image-turbo-pipeline/resolve/main/text_encoder_2/model.safetensors
- Command line
-
hf download hf://Bl4ckSpaces/z-image-turbo-pipeline/text_encoder_2/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Bl4ckSpaces/z-image-turbo-pipeline/resolve/main/text_encoder_2/model.safetensors
2.82 GB
- Xet hash:
- dbff92bd71a3fc106cdb76062a90b1a141a9b15c7175eca51f957560c172eddb
- Size of remote file:
- 2.82 GB
- SHA256:
- 2eae2b2028befc4a1a24760858a37c09d39cc5c3d93b832f9dd785a47cd6c7fa
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