Model reference · open weights
AuraSR is an open-weight image model from fal. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Released by | fal |
|---|---|
| Type | Image models |
| Task | Image edit |
| Parameters (lead) | 618M |
| Runs with | transformers |
| Released | 2024-07-29 |
| Popularity | 787 downloads / month |
| Licence | Open weights |
About
GAN-based Super-Resolution for upscaling generated images, a variation of the GigaGAN paper for image-conditioned upscaling. Torch implementation is based on the unofficial lucidrains/gigagan-pytorch repository.
$ pip install aura-sr
from aura_sr import AuraSR
aura_sr = AuraSR.from_pretrained("fal/AuraSR-v2")
import requests
from io import BytesIO
from PIL import Image
def load_image_from_url(url):
response = requests.get(url)
image_data = BytesIO(response.content)
return Image.open(image_data)
image = load_image_from_url("https://mingukkang.github.io/GigaGAN/static/images/iguana_output.jpg").resize((256, 256))
upscaled_image = aura_sr.upscale_4x_overlapped(image)
From the published model card. Full card on the HuggingFace links in the sidebar.
How it works
Using it via the API
Once AxForge deploys aurasr for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (aurasr below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/images/generations \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"aurasr","prompt":"a red bicycle","size":"1024x1024"}'
Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.