Instructions to use danishjaved/Lisa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use danishjaved/Lisa with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lodestones/Chroma", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("danishjaved/Lisa") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 495 Bytes
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tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/1755858599038__000001750_0.jpg
text: '-'
- output:
url: images/1755859162370__000002000_0.jpg
text: '-'
base_model: lodestones/Chroma
instance_prompt: model1
license: apache-2.0
---
# Asian model
<Gallery />
## Trigger words
You should use `model1` to trigger the image generation.
## Download model
[Download](/danishjaved/Lisa/tree/main) them in the Files & versions tab.
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