Text-to-Image
Diffusers
English
Text-to-Image
IP-Adapter
Flux.1-dev
image-generation
Stable Diffusion
Instructions to use InstantX/FLUX.1-dev-IP-Adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use InstantX/FLUX.1-dev-IP-Adapter with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("InstantX/FLUX.1-dev-IP-Adapter", 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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README.md
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# FLUX.1-dev-IP-Adapter
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This repository contains a IP-Adapter for FLUX.1-dev model released by researchers from [InstantX Team](https://huggingface.co/InstantX), we hope you
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# Showcases
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# Inference
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# Limitations
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This model supports image reference, but is not perfect for style transfer, which means that there exists a trade-off between content leakage and style transfer. We don't find similar properties in FLUX.1-dev (DiT-based) as in [InstantStyle](https://instantstyle.github.io/) (UNet-based). It may take several attempts to get satisfied results. Furthermore, current released model may suffer from limited diversity, thus cannot cover some styles or concepts.
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# FLUX.1-dev-IP-Adapter
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This repository contains a IP-Adapter for FLUX.1-dev model released by researchers from [InstantX Team](https://huggingface.co/InstantX), where image work just like text, so it may not be responsive or interfere with other text, but we do hope you enjoy this model, have fun and share your creative works with us [on Twitter](https://x.com/instantx_ai).
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# Showcases
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<div class="container">
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<img src="./assets/teasers/0.png" width="1024"/>
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<img src="./assets/teasers/1.png" width="1024"/>
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<img src="./assets/teasers/2.png" width="1024"/>
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<img src="./assets/teasers/3.png" width="1024"/>
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<img src="./assets/teasers/4.png" width="1024"/>
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<img src="./assets/teasers/5.png" width="1024"/>
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<img src="./assets/teasers/6.png" width="1024"/>
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<img src="./assets/teasers/7.png" width="1024"/>
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<img src="./assets/teasers/8.png" width="1024"/>
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</div>
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# Inference
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```python
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# TODO
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```
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# Limitations
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This model supports image reference, but is not perfect for style transfer, which means that there exists a trade-off between content leakage and style transfer. We don't find similar properties in FLUX.1-dev (DiT-based) as in [InstantStyle](https://instantstyle.github.io/) (UNet-based). It may take several attempts to get satisfied results. Furthermore, current released model may suffer from limited diversity, thus cannot cover some styles or concepts.
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