--- base_model: black-forest-labs/FLUX.1-dev library_name: diffusers license: other tags: - text-to-image - diffusers-training - diffusers - lora - flux - flux-diffusers - template:sd-lora - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers-training - diffusers - lora - flux - flux-diffusers - template:sd-lora instance_prompt: A portrait photo of sks blupus the cat widget: [] --- # Flux DreamBooth LoRA - strickvl/flux-dreambooth-blupus ## Model description These are strickvl/flux-dreambooth-blupus 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? False. ## Trigger words You should use `A portrait photo of sks blupus the cat` to trigger the image generation. ## Download model [Download the *.safetensors LoRA](strickvl/flux-dreambooth-blupus/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('strickvl/flux-dreambooth-blupus', weight_name='pytorch_lora_weights.safetensors') image = pipeline('A portrait photo of sks blupus the cat').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]