Instructions to use guillekenzo/aros-994ab152-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use guillekenzo/aros-994ab152-R with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krea/Krea-2-Raw", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("guillekenzo/aros-994ab152-R") prompt = "A photo of ggfv person on a wooden table indoors." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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base_model: krea/Krea-2-Raw
tags:
- text-to-image
- diffusers
- lora
- krea2
- template:sd-lora
license: apache-2.0
instance_prompt: "ggfv person"
widget:
- text: "A photo of ggfv person on a wooden table indoors."
output:
url: sample_0.png
- text: "A photo of ggfv person outdoors on a patch of grass."
output:
url: sample_1.png
- text: "A close-up photo of ggfv person against a plain background."
output:
url: sample_2.png
---
# Krea 2 LoRA — guillekenzo/aros-994ab152-R
<Gallery />
A DreamBooth-LoRA for **Krea 2**, trained on **Krea 2 RAW** and shown on **Krea 2 Turbo**. The samples below were generated with this LoRA on Turbo (8 steps).
## Trigger
Use the token `ggfv person` to invoke the concept.
## Samples

> *"A photo of ggfv person on a wooden table indoors."*

> *"A photo of ggfv person outdoors on a patch of grass."*

> *"A close-up photo of ggfv person against a plain background."*
## Use it with diffusers
```py
import torch
from diffusers import Krea2Pipeline
pipe = Krea2Pipeline.from_pretrained("krea/Krea-2-Turbo", torch_dtype=torch.bfloat16).to("cuda")
pipe.load_lora_weights("guillekenzo/aros-994ab152-R")
image = pipe("A photo of ggfv person on a wooden table indoors.", num_inference_steps=8, guidance_scale=0.0).images[0]
image.save("output.png")
```
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