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
File size: 580 Bytes
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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
<Gallery />
## 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](/ovieyra21/sdxlr-mabama/tree/main) them in the Files & versions tab.
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