SDXL LoRA DreamBooth - multimodalart/poli-multiplier-75-face-repeats-4-pivot-75
![](https://huggingface.co/multimodalart/poli-multiplier-75-face-repeats-4-pivot-75/resolve/main/image-0.png)
- Prompt
- A photo of <s0><s1> a man wearing headphones and a blue shirt
![](https://huggingface.co/multimodalart/poli-multiplier-75-face-repeats-4-pivot-75/resolve/main/image-1.png)
- Prompt
- A photo of <s0><s1> a bald man wearing glasses and a white t - shirt
![](https://huggingface.co/multimodalart/poli-multiplier-75-face-repeats-4-pivot-75/resolve/main/image-2.png)
- Prompt
- A photo of <s0><s1> a man with glasses and a beard smiles
![](https://huggingface.co/multimodalart/poli-multiplier-75-face-repeats-4-pivot-75/resolve/main/image-3.png)
- Prompt
- A photo of <s0><s1> a bald man with glasses and a colorful shirt
![](https://huggingface.co/multimodalart/poli-multiplier-75-face-repeats-4-pivot-75/resolve/main/image-4.png)
- Prompt
- A photo of <s0><s1> a man with glasses and a hat wearing an orange cap
![](https://huggingface.co/multimodalart/poli-multiplier-75-face-repeats-4-pivot-75/resolve/main/image-5.png)
- Prompt
- A photo of <s0><s1> a man wearing glasses and a yellow hat taking a selfie
Model description
These are multimodalart/poli-multiplier-75-face-repeats-4-pivot-75 LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
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 TOK
→ use <s0><s1>
in your prompt
Use it with the 🧨 diffusers library
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('multimodalart/poli-multiplier-75-face-repeats-4-pivot-75', weight_name='pytorch_lora_weights.safetensors')
embedding_path = hf_hub_download(repo_id='multimodalart/poli-multiplier-75-face-repeats-4-pivot-75', filename="embeddings.safetensors", repo_type="model")
state_dict = load_file(embedding_path)
pipeline.load_textual_inversion(state_dict["clip_l"], token=["<s0>", "<s1>"], text_encoder=pipeline.text_encoder, tokenizer=pipeline.tokenizer)
pipeline.load_textual_inversion(state_dict["clip_g"], token=["<s0>", "<s1>"], text_encoder=pipeline.text_encoder_2, tokenizer=pipeline.tokenizer_2)
image = pipeline('A photo of <s0><s1>').images[0]
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
Download model
Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
- Download the LoRA *.safetensors here. Rename it and place it on your Lora folder.
- Download the text embeddings *.safetensors here. Rename it and place it on it on your embeddings folder.
All Files & versions.
Details
The weights were trained using 🧨 diffusers Advanced Dreambooth Training Script.
LoRA for the text encoder was enabled. False.
Pivotal tuning was enabled: True.
Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
- Downloads last month
- 2
Model tree for multimodalart/poli-multiplier-75-face-repeats-4-pivot-75
Base model
stabilityai/stable-diffusion-xl-base-1.0
Adapter
this model