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Sponsored by
Vmake Labs Video Enhancer
multimodalart / public-domain-mouse-all
Model's Last Updated: January 01 2024
text-to-image
Introduction of public-domain-mouse-all
Model Details of public-domain-mouse-all
SDXL LoRA DreamBooth - multimodalart/public-domain-mouse-all
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
- Prompt
- A <s0><s1> mouse character
Model description
These are multimodalart/public-domain-mouse-all 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
public-domain-mouse-all.safetensorshere 💾 .-
Place it on your
models/Lorafolder. -
On AUTOMATIC1111, load the LoRA by adding
<lora:public-domain-mouse-all:1>to your prompt. On ComfyUI just load it as a regular LoRA .
-
Place it on your
-
Embeddings
: download
public-domain-mouse-all_emb.safetensorshere 💾 .-
Place it on it on your
embeddingsfolder -
Use it by adding
public-domain-mouse-all_embto your prompt. For example,A public-domain-mouse-all_emb mouse character(you need both the LoRA and the embeddings as they were trained together for this LoRA)
-
Place it on it on your
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/public-domain-mouse-all', weight_name='pytorch_lora_weights.safetensors')
embedding_path = hf_hub_download(repo_id='multimodalart/public-domain-mouse-all', filename='public-domain-mouse-all_emb.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 <s0><s1> mouse character').images[0]
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
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
Details
All Files & versions .
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.
Runs of multimodalart public-domain-mouse-all on huggingface.co
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3-day runs
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30-day runs
More Information About public-domain-mouse-all huggingface.co Model
Url of public-domain-mouse-all
public-domain-mouse-all huggingface.co Url
Provider of public-domain-mouse-all huggingface.co
Other API from multimodalart
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