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", 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
File size: 946 Bytes
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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
<Gallery />
## 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](/biali/sdv15_loras/tree/main) them in the Files & versions tab.
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