Instructions to use mindlywork/Maskot1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mindlywork/Maskot1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("mindlywork/Maskot1") prompt = "Maskot1" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
widget:
- text: Maskot1
output:
url: images/out-0 (12).png
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: Maskot1
license: cc
Maskot1
.png)
- Prompt
- Maskot1
Model description
Maskot1
Trigger words
You should use Maskot1 to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.