Instructions to use yur1xfd/a3d_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yur1xfd/a3d_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("ckpt/In-Context-LoRA", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("yur1xfd/a3d_lora") prompt = "This is a four-panel image which illustrates a pair of geometrically aligned objects in front and back side views. The [TOP-LEFT] shows a <cat animal> from the front side view. The [TOP-RIGHT] shows the same <cat animal> from the back side view. The [BOTTOM-LEFT] shows a <dog animal> from the front side view. The [BOTTOM-RIGHT] shows the same <dog animal> from the front side view." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: >-
This is a four-panel image which illustrates a pair of geometrically
aligned objects in front and back side views. The [TOP-LEFT] shows a <cat
animal> from the front side view. The [TOP-RIGHT] shows the same <cat
animal> from the back side view. The [BOTTOM-LEFT] shows a <dog animal>
from the front side view. The [BOTTOM-RIGHT] shows the same <dog animal>
from the front side view.
parameters:
negative_prompt: '-'
output:
url: images/photo_2025-05-21_13-47-59.jpg
base_model: ckpt/In-Context-LoRA
instance_prompt: null
license: mit
a3d_lora

- Prompt
- This is a four-panel image which illustrates a pair of geometrically aligned objects in front and back side views. The [TOP-LEFT] shows a <cat animal> from the front side view. The [TOP-RIGHT] shows the same <cat animal> from the back side view. The [BOTTOM-LEFT] shows a <dog animal> from the front side view. The [BOTTOM-RIGHT] shows the same <dog animal> from the front side view.
- Negative Prompt
- -
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.