Instructions to use dimitribarbot/Z-Image-Turbo-int8wo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dimitribarbot/Z-Image-Turbo-int8wo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dimitribarbot/Z-Image-Turbo-int8wo", 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 diffusion_pytorch_model.bin from dimitribarbot/Z-Image-Turbo-int8wo: direct link, hf CLI and curl.
- Browser
- Download file 6.17 GB
-
https://huggingface.co/dimitribarbot/Z-Image-Turbo-int8wo/resolve/main/diffusion_pytorch_model.bin
- Command line
-
hf download hf://dimitribarbot/Z-Image-Turbo-int8wo/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/dimitribarbot/Z-Image-Turbo-int8wo/resolve/main/diffusion_pytorch_model.bin
6.17 GB
- Xet hash:
- fc8559a589aff336269f60c60f79214a5d6cf5cb75ff32839b14c100aab5189d
- Size of remote file:
- 6.17 GB
- SHA256:
- a784eda95b7b0f84f84f3a66b68ae467a93954ef6ce5210b7e0aab90d38c9d7d
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