Instructions to use xuminglong/kontext-tryon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xuminglong/kontext-tryon with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("xuminglong/kontext-tryon") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Add proper tags
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by multimodalart HF Staff - opened
README.md
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license: mit
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base_model:
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https://www.runninghub.cn/post/1944965304159232001/?inviteCode=kol01-rh0102
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可本地部署
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license: mit
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base_model:
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pipeline_tag: image-to-image
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tags:
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- lora
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- diffusers
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- flux
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https://www.runninghub.cn/post/1944965304159232001/?inviteCode=kol01-rh0102
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可本地部署
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