Instructions to use YuCollection/FLUX.1-schnell-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use YuCollection/FLUX.1-schnell-Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("YuCollection/FLUX.1-schnell-Diffusers", 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
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> The model is released under the **Apache License, Version 2.0**, which permits use, modification, and redistribution under its terms.
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> **Cooperation Notice:**
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> The maintainer will cooperate in good faith with the original rights holder or upstream maintainers, consistent with the Apache License 2.0.
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> Requests may be submitted via **Discussions**.
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> *This repository is not affiliated with or endorsed by Black Forest Labs.*
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`FLUX.1 [schnell]` is a 12-billion-parameter rectified flow transformer capable of generating high-quality images from text descriptions.
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> The model is released under the **Apache License, Version 2.0**, which permits use, modification, and redistribution under its terms.
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> *This repository is not affiliated with or endorsed by Black Forest Labs.*
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> The maintainer is willing to cooperate in good faith with the original rights holder regarding reasonable requests.
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`FLUX.1 [schnell]` is a 12-billion-parameter rectified flow transformer capable of generating high-quality images from text descriptions.
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