Instructions to use vipuldeore/foreigner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vipuldeore/foreigner 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("vipuldeore/foreigner") prompt = "photo realistic, 30mm amateur photo, natural detailed skin, blonde bikinim1 woman , wearing a turtleneck dress sitting in a cafe having a coffee, looking at viewer, smiling <lora:bikinim1_flux_v1:1.3>" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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bikinim1_flux_v1.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:341076066e09c344e3216e625c9c672a6005eb1e7f7434ad5f741c6dffd55d17
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size 343805543
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images/00190-3214970463.png
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Git LFS Details
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