---
base_model: black-forest-labs/FLUX.1-dev
library_name: diffusers
license: other
widget:
- text: >-
    a bustling manga street, devoid of vehicles, detailed with vibrant colors
    and dynamic line work, characters in the background adding life and
    movement, under a soft golden hour light, with rich textures and a lively
    atmosphere, high resolution, sharp focus
  output:
    url: images/example_v9pjueoq1.png
- text: >-
    a boat in the canals of Venice, painted in gouache with soft, flowing
    brushstrokes and vibrant, translucent colors, capturing the serene
    reflection on the water under a misty ambiance, with rich textures and a
    dynamic perspective
  output:
    url: images/example_jx5b3cugc.png
- text: >-
    A vibrant orange poppy flower, enclosed in an ornate golden frame, against a
    black backdrop, rendered in anime style with bold outlines, exaggerated
    details, and a dramatic chiaroscuro lighting.
  output:
    url: images/example_tphrlr123.png
- text: >-
    Armored armadillo, detailed anatomy, precise shading, labeled diagram,
    cross-section, high resolution.
  output:
    url: images/example_5cml5u298.png
- text: A photographic photo of a hedgehog in a forest 4k
  output:
    url: images/example_9tr56cjcn.png
- text: >-
    Grainy shot of a robot cooking in the kitchen, with soft shadows and
    nostalgic film texture.
  output:
    url: images/example_brq7cz6kd.png
tags:
- text-to-image
- diffusers-training
- diffusers
- lora
- flux
- flux-diffusers
- template:sd-lora
- text-to-image
- diffusers-training
- diffusers
- lora
- flux
- flux-diffusers
- template:sd-lora
datasets:
- data-is-better-together/image-preferences-results-binarized
- data-is-better-together/open-image-preferences-v1-results

---

<!-- 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. -->


# Flux DreamBooth LoRA - data-is-better-together/image-preferences-flux-dev-lora

<Gallery />

## Model description

These are davidberenstein1957/image-preferences-flux-schnell-lora DreamBooth LoRA weights for black-forest-labs/FLUX.1-schnell.

The weights were trained using [DreamBooth](https://dreambooth.github.io/) with the [Flux diffusers trainer](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/README_flux.md).

Was LoRA for the text encoder enabled? False.

## Trigger words

You should use `["Cinematic", "Photographic", "Anime", "Manga", "Digital art", "Pixel art", "Fantasy art", "Neonpunk", "3D Model", “Painting”, “Animation” “Illustration”]` to trigger the image generation.

## Download model

[Download the *.safetensors LoRA](davidberenstein1957/image-preferences-flux-schnell-dev/tree/main) in the Files & versions tab.

## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)

```py
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('davidberenstein1957/image-preferences-flux-dev-lora', weight_name='pytorch_lora_weights.safetensors')
image = pipeline('["Cinematic", "Photographic", "Anime", "Manga", "Digital art", "Pixel art", "Fantasy art", "Neonpunk", "3D Model", “Painting”, “Animation” “Illustration”]').images[0]
```

For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)

## License

Please adhere to the licensing terms as described [here](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md).


## 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]