File size: 2,054 Bytes
b1e504e f11fd02 b1e504e 2cd8588 b1e504e f11fd02 b1e504e f11fd02 b1e504e f11fd02 b1e504e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 |
---
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")
``` |