--- license: apache-2.0 tags: - text-to-image --- # AuraFlow v0.3 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6311151c64939fabc00c8436/BcH5xyGCGNnkmPC-OPS9z.png) 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") ```