Instructions to use Runware/TwinFlow-Z-Image-Turbo-exp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Runware/TwinFlow-Z-Image-Turbo-exp with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Runware/TwinFlow-Z-Image-Turbo-exp", 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
update pipe and transformers class name
Browse files- model_index.json +2 -2
model_index.json
CHANGED
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@@ -1,5 +1,5 @@
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{
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"_class_name": "
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"_diffusers_version": "0.36.0.dev0",
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"scheduler": [
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"diffusers",
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],
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"transformer": [
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"diffusers",
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"
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],
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"vae": [
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"diffusers",
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{
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"_class_name": "ZImageTwinPipeline",
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"_diffusers_version": "0.36.0.dev0",
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"scheduler": [
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"diffusers",
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],
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"transformer": [
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"diffusers",
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"ZImageTransformer2DModelWrapper"
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],
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"vae": [
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"diffusers",
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