Instructions to use gitgato/yebama-v2-flux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gitgato/yebama-v2-flux 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("gitgato/yebama-v2-flux") prompt = "high-resolution photo of a yebama, photorealistic, UHD, optimal photography, natural lighting, shot on a Sony A&III " image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
yebama-v2-flux

- Prompt
- high-resolution photo of a yebama, photorealistic, UHD, optimal photography, natural lighting, shot on a Sony A&III
- Negative Prompt
- low quality
Model description
yeba
Trigger words
You should use yebama 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 gitgato/yebama-v2-flux
Base model
black-forest-labs/FLUX.1-dev