| --- |
| base_model: black-forest-labs/FLUX.1-dev |
| library_name: diffusers |
| license: other |
| instance_prompt: <skswr> |
| widget: |
| - text: A photo of <skswr>, studio lighting, standing up |
| output: |
| url: image_0.png |
| - text: A photo of <skswr>, studio lighting, standing up |
| output: |
| url: image_1.png |
| - text: A photo of <skswr>, studio lighting, standing up |
| output: |
| url: image_2.png |
| - text: A photo of <skswr>, studio lighting, standing up |
| output: |
| url: image_3.png |
| tags: |
| - text-to-image |
| - diffusers-training |
| - diffusers |
| - lora |
| - flux |
| - flux-diffusers |
| - template:sd-lora |
| --- |
| |
| <!-- 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 - hb23/sample_data |
| |
| <Gallery /> |
| |
| ## Model description |
| |
| These are hb23/sample_data DreamBooth LoRA weights for black-forest-labs/FLUX.1-dev. |
|
|
| 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? True. |
|
|
| ## Trigger words |
|
|
| You should use `<skswr>` to trigger the image generation. |
|
|
| ## Download model |
|
|
| [Download the *.safetensors LoRA](hb23/sample_data/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('hb23/sample_data', weight_name='pytorch_lora_weights.safetensors') |
| image = pipeline('A photo of <skswr>, studio lighting, standing up').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] |
