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
- Draw Things
- DiffusionBee
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# FLUX.1 [schnell]
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> **Note:** This is an **archived
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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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# FLUX.1 [schnell]
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> **Note:** This repository is an **archived mirror** and is **not** the original upstream source.
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> The original model, weights, and documentation are developed and maintained by **Black Forest Labs**.
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> This mirror is provided for convenience and preservation purposes only.
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> The model weights are **unmodified**. Minor editorial changes may have been made to this README (e.g., formatting or clarification) and do **not** alter the model, its behavior, or its licensing.
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> The model is released under the **Apache License, Version 2.0**, which permits use, reproduction, modification, and redistribution, including for commercial purposes, subject to the terms of the license.
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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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