Instructions to use diffusers/FLUX.1-dev-torchao-int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers/FLUX.1-dev-torchao-int8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers/FLUX.1-dev-torchao-int8", 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
- Draw Things
- DiffusionBee
Update README.md
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README.md
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@@ -83,5 +83,5 @@ pipe = FluxPipeline.from_pretrained(
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# safe_serialization set to `False` as we can't save torchao quantized model to safetensors format
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pipe.save_pretrained("FLUX.1-dev-torchao-
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```
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# safe_serialization set to `False` as we can't save torchao quantized model to safetensors format
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pipe.save_pretrained("FLUX.1-dev-torchao-int4", safe_serialization=False)
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```
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