SD1_5_Rank_8_CulText_8k

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LoRA text2image fine-tuning - iiiiDeal/SD1_5_Rank_8_CulText_8k

These are LoRA adaption weights for sd-legacy/stable-diffusion-v1-5. The weights were fine-tuned on the None dataset.

Intended uses & limitations

How to use

import torch
from diffusers import StableDiffusionPipeline


model_path = "iiiiDeal/SD1_5_Rank_8_CulText_8k"
prompt = "A high resolution image of a modern security checkpoint in China, featuring bilingual signage, uniformed personnel, and sleek architectural design."
pipe = StableDiffusionPipeline.from_pretrained("sd-legacy/stable-diffusion-v1-5", torch_dtype=torch.float16).to("cuda")

image = pipe(prompt, num_inference_steps=50, guidance_scale=7.5).images[0]
image.save("samples/pretrain.png")


pipe.unet.load_attn_procs(model_path)

image = pipe(prompt, num_inference_steps=50, guidance_scale=7.5).images[0]
image.save("samples/finetune.png")

Limitations and bias

[TODO: provide examples of latent issues and potential remediations]

Training details

[TODO: describe the data used to train the model]