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chinh102/onepiece-sdxlv1
onepiece-sdxlv1 is a text-to-image model from chinh102. 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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.safetensors186 MB · 98%
From the Hugging Face model README
onepiece-sdxlv1.safetensors here 💾.
models/Lora folder.<lora:onepiece-sdxlv1:1> to your prompt. On ComfyUI just load it as a regular LoRA.onepiece-sdxlv1_emb.safetensors here 💾.
embeddings folderonepiece-sdxlv1_emb to your prompt. For example, a photo of onepiece-sdxlv1_emb luffy gear 5
(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('chinh102/onepiece-sdxlv1', weight_name='pytorch_lora_weights.safetensors')
embedding_path = hf_hub_download(repo_id='chinh102/onepiece-sdxlv1', filename='onepiece-sdxlv1_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('Anime illustration of Luffy Gear 5: white cloud-like hair, open white jacket, purple shorts. Dynamic pose against night sky with full moon or clouds. Joyful expression, wide grin. Cartoonishly flexible body, stretched limbs. Glowing effects around figure. Energetic movement, mid-jump or playful stance. Contrast between illuminated character and dark background.').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 TOK → 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.