Instructions to use wkplhc/avcover with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wkplhc/avcover 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("wkplhc/avcover") prompt = "漫改av封面,With a beautiful wife, the cover of the diffuse av shows the real style of the wife and the black-and-white diffuse style in the picture respectively." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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- Prompt
- 漫改av封面,With a beautiful wife, the cover of the diffuse av shows the real style of the wife and the black-and-white diffuse style in the picture respectively.
Trigger words
You should use 漫改av封面 to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for wkplhc/avcover
Base model
black-forest-labs/FLUX.1-dev