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BruBel/lor-style-training-v5
lor-style-training-v5 is a text-to-image model from BruBel. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as openrail++.
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From the Hugging Face model README
lor-style-training-v5.safetensors here 💾.
models/Lora folder.<lora:lor-style-training-v5:1> to your prompt. On ComfyUI just load it as a regular LoRA.lor-style-training-v5_emb.safetensors here 💾.
embeddings folderlor-style-training-v5_emb to your prompt. For example, In lor-style-training-v5_emb style.
(you need both the LoRA and the embeddings as they were trained together for this LoRA)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('BruBel/lor-style-training-v5', weight_name='pytorch_lora_weights.safetensors')
embedding_path = hf_hub_download(repo_id='BruBel/lor-style-training-v5', filename='lor-style-training-v5_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 mage situated in a red sky, war scenario. The mage wears a purple cape. They radiate a leadership aura, with a calmly expression. It also has a staff as weapon. In <s0><s1> style.').images[0]
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
To trigger image generation of trained concept(or concepts) replace each concept identifier in you prompt with the new inserted tokens:
to trigger concept LEGENDSOFRUNETERRA → use <s0><s1> in your prompt
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.