Model reference · open weights

AuraFlow

Available as managed deployment Image fal Text→image 1 variants 991 dl/mo

AuraFlow 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 byfal
TypeImage models
TaskText→image
Parameters (lead)6.9B
Runs withdiffusers
Released2024-08-14
Popularity991 downloads / month
LicenceOpen weights

About

What AuraFlow is

AuraFlow v0.3 is the fully open-sourced flow-based text-to-image generation model. The model was trained with more compute compared to the previous version, AuraFlow-v0.2.

Compared to AuraFlow-v0.2, the model is fine-tuned on more aesthetic datasets and now supports various aspect ratio, (now width and height up to 1536 pixels).

This model achieves state-of-the-art results on GenEval. Read our blog post for more technical details. You can also check out the comparison with other models on this gallery page.

The model is currently in beta. We are working on improving it and the community's feedback is important.

Credits: A huge thank you to @cloneofsimo and @isidentical for bringing this project to life. It's incredible what two cracked engineers can achieve in such a short period of time. We also extend our gratitude to the incredible researchers whose prior work laid the foundation for our efforts.

Read the full model card

Usage

$ pip install transformers accelerate protobuf sentencepiece
$ pip install git+https://github.com/huggingface/diffusers.git
from diffusers import AuraFlowPipeline
import torch

pipeline = AuraFlowPipeline.from_pretrained(
    "fal/AuraFlow-v0.3",
    torch_dtype=torch.float16,
    variant="fp16",
).to("cuda")

image = pipeline(
    prompt="rempage of the iguana character riding F1, fast and furious, cinematic movie poster",
    width=1536,
    height=768,
    num_inference_steps=50,
    generator=torch.Generator().manual_seed(1),
    guidance_scale=3.5,
).images[0]

image.save("output.png")

From the published model card. Full card on the HuggingFace links in the sidebar.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys fal-auraflow for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (fal-auraflow 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":"fal-auraflow","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.

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