Instructions to use ali-vilab/In-Context-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ali-vilab/In-Context-LoRA 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.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ali-vilab/In-Context-LoRA") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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README.md
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📢 [[Project Page](https://ali-vilab.github.io/In-Context-LoRA-Page/)] [[Github Repo](https://github.com/ali-vilab/In-Context-LoRA)] [[Paper](https://arxiv.org/abs/2410.23775)]
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# Model Summary
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In-Context LoRA fine-tunes text-to-image models to generate image sets with customizable intrinsic relationships, optionally conditioned on another set using SDEdit. It can be adapted to a wide range of tasks
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This model hub includes In-Context LoRA models across 10 tasks. [MODEL ZOO](#model-zoo) details these models and their recommend settings. For more details on how these models are trained, please refer to our [paper](https://arxiv.org/abs/2410.23775).
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📢 [[Project Page](https://ali-vilab.github.io/In-Context-LoRA-Page/)] [[Github Repo](https://github.com/ali-vilab/In-Context-LoRA)] [[Paper](https://arxiv.org/abs/2410.23775)]
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# Model Summary
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In-Context LoRA fine-tunes text-to-image models (\textit{e.g.,} [FLUX](https://huggingface.co/black-forest-labs/FLUX.1-dev)) to generate image sets with customizable intrinsic relationships, optionally conditioned on another set using SDEdit. It can be adapted to a wide range of tasks
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This model hub includes In-Context LoRA models across 10 tasks. [MODEL ZOO](#model-zoo) details these models and their recommend settings. For more details on how these models are trained, please refer to our [paper](https://arxiv.org/abs/2410.23775).
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