Instructions to use fal/virtual-tryoff-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fal/virtual-tryoff-lora 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.2-klein-9B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("fal/virtual-tryoff-lora") prompt = "TRYOFF extract the t-shirt over a white background, product photography style. NO HUMAN VISIBLE (the garments maintain their 3D form like an invisible mannequin)." 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] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
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README.md
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@@ -73,6 +73,7 @@ Trained with [fal.ai trainer](https://fal.ai/models/fal-ai/flux-2-klein-9b-base-
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- Base model: FLUX.2-klein-base-9B
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- Steps: 10000
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- Learning Rate: 0.00005
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### Author
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Created by [Riza Velioglu](https://rizavelioglu.github.io/) at [fal.ai](https://fal.ai/)
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- Base model: FLUX.2-klein-base-9B
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- Steps: 10000
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- Learning Rate: 0.00005
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- Dataset: 300 image pairs (model + garment) of shape `1024x1024`
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### Author
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Created by [Riza Velioglu](https://rizavelioglu.github.io/) at [fal.ai](https://fal.ai/)
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