Instructions to use biali/sdv15_loras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use biali/sdv15_loras with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("biali/sdv15_loras") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/concept_3_2026-06-11-15-27-28.png
text: '-'
- output:
url: images/concept_2_2026-06-11-15-27-32.png
text: '-'
- output:
url: images/deserto_001_brown_ground.png
text: '-'
- output:
url: images/newmap_brown_ramp.png
text: '-'
base_model: stable-diffusion-v1-5/stable-diffusion-v1-5
instance_prompt: clifftex, gndtex, topdownmap
license: apache-2.0
SD v1.5 LoRAs for BrowJS

- Prompt
- -

- Prompt
- -

- Prompt
- -

- Prompt
- -
Model description
Just some quickly trained LoRAs to create things like map views (from top to bottom), seamless textures, etc.
Trigger words
You should use clifftex to trigger the image generation.
You should use gndtex to trigger the image generation.
You should use topdownmap to trigger the image generation.
Download model
Download them in the Files & versions tab.