--- tags: - stable-diffusion-xl - stable-diffusion-xl-diffusers - diffusers-training - text-to-image - diffusers - lora - template:sd-lora widget: - text: >- Photo of TREY cat as a guitarist, on stage, awesome, photorealistic, pyrotechnics, highly detailed output: url: download (3).png - text: a TREY cat on the floor output: url: image_0.png - text: a TREY cat on the floor output: url: image_1.png - text: a TREY cat on the floor output: url: image_2.png - text: Imagine TREY cat in an alien hellscape output: url: 7cf5c0e2-84a9-4d7a-91fc-40179b805c1b.jpeg base_model: stabilityai/stable-diffusion-xl-base-1.0 instance_prompt: photo of a TREY cat license: openrail++ pipeline_tag: text-to-image --- # SDXL LoRA DreamBooth - trey-cat-sdxl-lora ## Model description ### These are trey-cat-sdxl-lora LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. ## Download model ### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke - **LoRA**: download **[`trey-cat-sdxl-lora.safetensors` here ๐Ÿ’พ](/trey-cat-sdxl-lora/blob/main/trey-cat-sdxl-lora.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/). - *Embeddings*: download **[`trey-cat-sdxl-lora_emb.safetensors` here ๐Ÿ’พ](/trey-cat-sdxl-lora/blob/main/trey-cat-sdxl-lora_emb.safetensors)**. - Place it on it on your `embeddings` folder - Use it by adding `trey-cat-sdxl-lora_emb` to your prompt. For example, `photo of a TREY cat` (you need both the LoRA and the embeddings as they were trained together for this LoRA) ## Use it with the [๐Ÿงจ diffusers library](https://github.com/huggingface/diffusers) ```py from diffusers import AutoPipelineForText2Image import torch from huggingface_hub import hf_hub_download from safetensors.torch import load_file pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda') pipeline.load_lora_weights('trey-cat-sdxl-lora', weight_name='pytorch_lora_weights.safetensors') embedding_path = hf_hub_download(repo_id='trey-cat-sdxl-lora', filename='trey-cat-sdxl-lora_emb.safetensors', repo_type="model") state_dict = load_file(embedding_path) pipeline.load_textual_inversion(state_dict["clip_l"], token=[], text_encoder=pipeline.text_encoder, tokenizer=pipeline.tokenizer) pipeline.load_textual_inversion(state_dict["clip_g"], token=[], text_encoder=pipeline.text_encoder_2, tokenizer=pipeline.tokenizer_2) image = pipeline('a TREY cat on the floor').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 To trigger image generation of trained concept(or concepts) replace each concept identifier in you prompt with the new inserted tokens: to trigger concept `Trey cat` โ†’ use `TREY cat` in your prompt ## Details All [Files & versions](/trey-cat-sdxl-lora/tree/main). The weights were trained using [๐Ÿงจ 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: True. Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.