242-continuous-subject-specific-attribute-control-in-t2i-models-by-identifying-semantic-directions

https://github.com/szu-advtech-2024/242-continuous-subject-specific-attribute-control-in-t2i-models-by-identifying-semantic-directions

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Citation

https://github.com/SZU-AdvTech-2024/242-Continuous-Subject-Specific-Attribute-Control-in-T2I-Models-by-Identifying-Semantic-Directions/blob/main/

# Continuous, Subject-Specific Attribute Control in T2I Models by Identifying Semantic Directions

## 

,(Text to Image,T2I).,(""),.,,.,CLIP,.,,.,(),,.

## 

Githubhttps://github.com/CompVis/attribute-control

READMEREADME



## 



- python3.9.20
- CUDA 12.4

requirements.txt



```bash
pip install -r requirements.txt
```

## 

stable-diffusion-xl-base-1.0

## 



```bash
python learn_delta.py device=cuda:0 model=sdxl prompts=people/age
```



```bash
python learn_delta.py device=cuda:0 model=sdxl prompts=people/age model.compile=False +model.gradient_checkpointing=True
```

## 

notebooks/inference_sdxl.ipynbblock3

```python
state_dict = torch.load('enter your delta result here')
#
```

## 



- pretrained_deltas

- outputs

  - outputs\learn_delta\people\age\runs\2024-11-24\02-28-23

    - 

      ```python
      #
      max_steps: 1000
      batch_size: 1
      grad_accum_steps: 8
      scale_batch_size: 4
      ```

  - outputs\learn_delta\people\age\runs\2024-12-06\14-25-43

    - 

      ```python
      #
      max_steps: 2000
      batch_size: 1
      grad_accum_steps: 8
      scale_batch_size: 4
      ```

  - outputs\learn_delta\people\age\runs\2025-01-07\07-35-18

    - 

      ```python
      #
      max_steps: 1000
      batch_size: 1
      grad_accum_steps: 5
      scale_batch_size: 4
      ```

  - outputs\learn_delta\people\age\runs\2025-01-08\08-57-38

    - 

      ```python
      #
      max_steps: 500
      batch_size: 1
      grad_accum_steps: 8
      scale_batch_size: 4
      ```

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  • Login: SZU-AdvTech-2024
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