Instructions to use fal/FLUX.2-dev-Turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fal/FLUX.2-dev-Turbo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.2-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("fal/FLUX.2-dev-Turbo") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Fix diffusers code example
Browse files
README.md
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@@ -56,7 +56,7 @@ pipe = Flux2Pipeline.from_pretrained(
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).to("cuda")
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pipe.load_lora_weights(
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"fal/FLUX.2-Turbo",
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weight_name="flux.2-turbo-lora.safetensors"
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)
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).to("cuda")
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pipe.load_lora_weights(
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"fal/FLUX.2-dev-Turbo",
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weight_name="flux.2-turbo-lora.safetensors"
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)
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