|
--- |
|
license: apache-2.0 |
|
tags: |
|
- text-to-image |
|
--- |
|
# AuraFlow v0.3 |
|
|
|
|
|
 |
|
|
|
|
|
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](https://huggingface.co/fal/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](https://blog.fal.ai/auraflow/) for more technical details. You can also check out the comparison with other models on this gallery [page](https://cloneofsimo.github.io/compare_aura_sd3/). |
|
|
|
The model is currently in beta. We are working on improving it and the community's feedback is important. |
|
Join [fal's Discord](https://discord.gg/fal-ai) to give us feedback and stay in touch with the model development. |
|
|
|
Credits: A huge thank you to [@cloneofsimo](https://twitter.com/cloneofsimo) and [@isidentical](https://twitter.com/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. |
|
|
|
## Usage |
|
|
|
```bash |
|
$ pip install transformers accelerate protobuf sentencepiece |
|
$ pip install git+https://github.com/huggingface/diffusers.git |
|
``` |
|
|
|
```python |
|
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") |
|
``` |
