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---
license: apache-2.0
language:
- en
library_name: diffusers
pipeline_tag: text-to-image
---
# Target-Driven Distillation
<div align="center">
[**Project Page**](https://tdd.github.io/tdd) **|** [**Paper**](https://arxiv.org/abs) **|** [**Code**](https://github.com/RedAIGC/Target-Driven-Distillation) **|** [🤗 **Gradio demo**](https://huggingface.co/spaces)
</div>
## Introduction
Target-Driven Distillation: Consistency Distillation with Target Timestep Selection and Decoupled Guidance
<div align="center">
<img src='teaser.jpg'>
</div>
## Update
[2024.08.22]:Upload the TDD LoRA weights of Stable Diffusion XL, YamerMIX and RealVisXL-V4.0, fast text-to-image generation.
- sdxl_tdd_lora_weights.safetensors
- yamermix_tdd_lora_weights.safetensors
- realvis_tdd_sdxl_lora_weights.safetensors
Thanks to [Yamer](https://civitai.com/user/Yamer) and [SG_161222](https://civitai.com/user/SG_161222) for developing [YamerMIX](https://civitai.com/models/84040?modelVersionId=395107) and [RealVisXL V4.0](https://civitai.com/models/139562/realvisxl-v40) respectively.
## Usage
You can directly download the model in this repository.
You also can download the model in python script:
```python
from huggingface_hub import hf_hub_download
hf_hub_download(repo_id="RedAIGC/TDD", filename="sdxl_tdd_lora_weights.safetensors", local_dir="./tdd_lora")
```
```python
# !pip install opencv-python transformers accelerate
import torch
import diffusers
from diffusers import StableDiffusionXLPipeline
from tdd_scheduler import TDDScheduler
device = "cuda"
tdd_lora_path = "tdd_lora/sdxl_tdd_lora_weights.safetensors"
pipe = StableDiffusionXLPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16").to(device)
pipe.scheduler = TDDSchedulerPlus.from_config(pipe.scheduler.config)
pipe.load_lora_weights(tdd_lora_path, adapter_name="accelerate")
pipe.fuse_lora()
prompt = "A photo of a cat made of water."
image = pipe(
prompt=prompt,
num_inference_steps=4,
guidance_scale=1.7,
eta=0.2,
generator=torch.Generator(device=device).manual_seed(546237),
).images[0]
image.save("tdd.png")
``` |