--- license: openrail++ library_name: diffusers tags: - text-to-image - stable-diffusion-xl - stable-diffusion-xl-diffusers - text-to-image - diffusers - lora - template:sd-lora base_model: runwayml/stable-diffusion-v1-5 instance_prompt: A mushroom in [V] style widget: - text: ' ' output: url: image_0.png - text: ' ' output: url: image_1.png - text: ' ' output: url: image_2.png --- # SDXL LoRA DreamBooth - abby101/test ## Model description ### These are abby101/test LoRA adaption weights for runwayml/stable-diffusion-v1-5. ## Download model ### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke - **LoRA**: download **[`..safetensors` here 💾](/abby101/test/blob/main/..safetensors)**. - Place it on your `models/Lora` folder. - On AUTOMATIC1111, load the LoRA by adding `` to your prompt. On ComfyUI just [load it as a regular LoRA](https://comfyanonymous.github.io/ComfyUI_examples/lora/). ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) ```py from diffusers import AutoPipelineForText2Image import torch pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda') pipeline.load_lora_weights('abby101/test', weight_name='pytorch_lora_weights.safetensors') image = pipeline('A mushroom in [V] style').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) ## Trigger words You should use A mushroom in [V] style to trigger the image generation. ## Details All [Files & versions](/abby101/test/tree/main). The weights were trained using [🧨 diffusers Advanced Dreambooth Training Script](https://github.com/huggingface/diffusers/blob/main/examples/advanced_diffusion_training/train_dreambooth_lora_sdxl_advanced.py). LoRA for the text encoder was enabled. False. Pivotal tuning was enabled: False. Special VAE used for training: None. ## 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]