Instructions to use ovieyra21/sdxlr-mabama with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ovieyra21/sdxlr-mabama with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ByteDance/SDXL-Lightning", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ovieyra21/sdxlr-mabama") prompt = "photo of a woman mab" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
widget:
- text: photo of a woman mab
parameters:
negative_prompt: Low quality
output:
url: images/premier.png
base_model: ByteDance/SDXL-Lightning
instance_prompt: mabama
license: mit
sdxlr-mabama

- Prompt
- photo of a woman mab
- Negative Prompt
- Low quality
Model description
mabama
Trigger words
You should use mabama to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.