Instructions to use LegoClipStars/Laval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LegoClipStars/Laval with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cagliostrolab/animagine-xl-3.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("LegoClipStars/Laval") prompt = "NEFT" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from LegoClipStars/Laval: direct link, hf CLI and curl.
- Browser
- Download file 584 Bytes
-
https://huggingface.co/LegoClipStars/Laval/resolve/main/README.md
- Command line
-
hf download hf://LegoClipStars/Laval/README.md
-
curl -L -o README.md https://huggingface.co/LegoClipStars/Laval/resolve/main/README.md
584 Bytes
metadata
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
widget:
- text: NEFT
parameters:
negative_prompt: animal hero
output:
url: images/Lavalthelion.jpg
base_model: cagliostrolab/animagine-xl-3.0
instance_prompt: Please spare me
license: cc-by-4.0
Laval

- Prompt
- NEFT
- Negative Prompt
- animal hero
Model description
Here's my RVC voice model of Laval from Legends of Chima.
Trigger words
You should use Please spare me to trigger the image generation.
Download model
Download them in the Files & versions tab.