README.md

---
base_model: Efficient-Large-Model/Sana_1600M_1024px_diffusers
library_name: diffusers
license: other
instance_prompt: a puppy, yarn art style
widget:
- text: a puppy in a pond, yarn art style
  output:
    url: image_0.png
- text: a puppy in a pond, yarn art style
  output:
    url: image_1.png
- text: a puppy in a pond, yarn art style
  output:
    url: image_2.png
- text: a puppy in a pond, yarn art style
  output:
    url: image_3.png
tags:
- text-to-image
- diffusers-training
- diffusers
- falqon
- sana
- sana-diffusers
---

<!-- 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 DreamBooth FALQON - wsl448/yarn_art_falqon_sana_block_int8_svd_lr2e-4

<Gallery />

## Model description

These are wsl448/yarn_art_falqon_sana_block_int8_svd_lr2e-4 DreamBooth FALQON weights for Efficient-Large-Model/Sana_1600M_1024px_diffusers.

The weights were trained using [DreamBooth](https://dreambooth.github.io/) with FALQON
(FP8-Accelerated LoRA with Quantization) for efficient fine-tuning.


## Trigger words

You should use `a puppy, yarn art style` to trigger the image generation.

## License

Please check the base model license.


## 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]