---
base_model: Efficient-Large-Model/Sana_1600M_1024px_BF16_diffusers
library_name: diffusers
license: other
inference: true
tags:
- sana
- sana-diffusers
- text-to-image
- diffusers
- control
- diffusers-training
---

<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->


# sana-edit-sayakpaul/omnisana-lr_1e-4-wd_0.0001-cd_0.0-scheduler_constant

These are Control weights trained on Efficient-Large-Model/Sana_1600M_1024px_BF16_diffusers and [TIGER-Lab/OmniEdit-Filtered-1.2M](https://huggingface.co/datasets/TIGER-Lab/OmniEdit-Filtered-1.2M).
You can find some example images below.

prompt: Give this the look of a traditional Japanese woodblock print.
![images_0)](./images_0.png)
prompt: transform the setting to a winter scene
![images_1)](./images_1.png)
prompt: Change it to look like it's in the style of an impasto painting.
![images_2)](./images_2.png)
prompt: turn the color of mushroom to gray
![images_3)](./images_3.png)


## License

Please adhere to the licensing terms as described [here](https://huggingface.co/Efficient-Large-Model/Sana_1600M_1024px_BF16_diffusers/blob/main/LICENSE.txt).


## Intended uses & limitations

#### How to use

```python
# TODO: add an example code snippet for running this diffusion pipeline
```

#### Limitations and bias

[TODO: provide examples of latent issues and potential remediations]

## Training details

[TODO: describe the data used to train the model]