Instructions to use AlejandroSossa/AstoriaV1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AlejandroSossa/AstoriaV1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xinsir/controlnet-union-sdxl-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("AlejandroSossa/AstoriaV1") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("xinsir/controlnet-union-sdxl-1.0", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("AlejandroSossa/AstoriaV1")
prompt = "-"
image = pipe(prompt).images[0]Astoria LoRa

- Prompt
- -

- Prompt
- -
Model description
a LoRa trained on a dataset of 20 pictures
Trigger words
You should use Astoria to trigger the image generation.
Download model
Download them in the Files & versions tab.
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Model tree for AlejandroSossa/AstoriaV1
Base model
xinsir/controlnet-union-sdxl-1.0