Instructions to use Jonjew/JenniferLawrence with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jonjew/JenniferLawrence 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("Jonjew/JenniferLawrence") prompt = "<lora:Jennifer_Lawrence_V2_Flux:1> this is a high definition image of a woman with a slightly sultry expression and striking, blonde hair cascading down her back, wearing a an elegant dress. She is standing in cafe looking at the viewer, smile" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Jennifer Lawrence

- Prompt
- <lora:Jennifer_Lawrence_V2_Flux:1> this is a high definition image of a woman with a slightly sultry expression and striking, blonde hair cascading down her back, wearing a an elegant dress. She is standing in cafe looking at the viewer, smile
Model description
FROM https://civitai.com/models/699054/jennifer-lawrence-flux?modelVersionId=979229
Strength 1
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Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for Jonjew/JenniferLawrence
Base model
black-forest-labs/FLUX.1-dev