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socialmedia-std-xl-base-1-0.safetensors here 💾.
models/Lora folder.<lora:socialmedia-std-xl-base-1-0:1> to your prompt. On ComfyUI just load it as a regular LoRA.socialmedia-std-xl-base-1-0_emb.safetensors here 💾.
embeddings foldersocialmedia-std-xl-base-1-0_emb to your prompt. For example, Create a promotional image for a SHOE SALE with bold black text near the bottom on a white and gray background. Include a red 50% OFF badge, a SHOP NOW button, sneakers, socks, and shoeboxes overlaying a gray diagonal strip. The design should have red cursive text and a liceria & co. logo in the top-left corner.
(you need both the LoRA and the embeddings as they were trained together for this LoRA)1from diffusers import AutoPipelineForText2Image
2import torch
3from huggingface_hub import hf_hub_download
4from safetensors.torch import load_file
5
6pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda')
7pipeline.load_lora_weights('javeriahassan/socialmedia-std-xl-base-1-0', weight_name='pytorch_lora_weights.safetensors')
8embedding_path = hf_hub_download(repo_id='javeriahassan/socialmedia-std-xl-base-1-0', filename='socialmedia-std-xl-base-1-0_emb.safetensors', repo_type="model")
9state_dict = load_file(embedding_path)
10pipeline.load_textual_inversion(state_dict["clip_l"], token=[], text_encoder=pipeline.text_encoder, tokenizer=pipeline.tokenizer)
11pipeline.load_textual_inversion(state_dict["clip_g"], token=[], text_encoder=pipeline.text_encoder_2, tokenizer=pipeline.tokenizer_2)
12
13image = pipeline('Design a promotional poster for AI chatbot integration services. The image should feature the text WARNER & SPENCER with a chatbot icon. Include bold text for AI CHATBOT and Integration Services, service details with checkmarks, and a Contact Us button on the left. A friendly chatbot graphic should be placed on the right side.').images[0]TOK → use <s0><s1> in your prompt