Instructions to use Norod78/sdxl-humeow-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Norod78/sdxl-humeow-lora 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("Norod78/sdxl-humeow-lora") prompt = "American gothic HuMeow " image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
SDXL-HuMeow-LoRA

- Prompt
- American gothic HuMeow

- Prompt
- Rick Sanchez HuMeow

- Prompt
- The Starry Night by Vincent van Gogh HuMeow

- Prompt
- The girl with a pearl earring HuMeow

- Prompt
- Wonderwoman HuMeow

- Prompt
- A socially awkward potato HuMeow

- Prompt
- A victorian HuMeow couple dancing together

- Prompt
- An astronaut HuMeow is riding a horse on mars

- Prompt
- An astronaut HuMeow is inside a spaceship

- Prompt
- The Mona Lisa HuMeow
(CivitAI)
Model description
As you all know, there are not enough cat images on the internet.
This HuMeow (Human + Meow) is an SDXL LoRA which was designed to help solve this problem by generating human(oid) cats as well as causing random cats to appear in scenes when the trigger word 'HuMeow' is used.
This LoRA was trained with CivitAI LoRA trainer upon images generated with MidJourney v6.
The training dataset is available for download
Trigger words
You should use HuMeow to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Use it with the 𧨠diffusers library
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('Norod78/sdxl-humeow-lora', weight_name='SDXL-HuMeow-LoRA-r8-000003.safetensors')
image = pipeline('The Mona Lisa HuMeow ').images[0]
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
- Downloads last month
- 30
Model tree for Norod78/sdxl-humeow-lora
Base model
stabilityai/stable-diffusion-xl-base-1.0