RohitGandikota commited on
Commit
ac5ee04
1 Parent(s): e0c992d

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +2 -2
app.py CHANGED
@@ -53,7 +53,7 @@ class Demo:
53
  with gr.Row():
54
 
55
  self.explain_infr = gr.Markdown(interactive=False,
56
- value='This is a demo of [Erasing Concepts from Stable Diffusion](https://erasing.baulab.info/). To try out a model where a concept has been erased, select a model and enter any prompt. For example, if you select the model "Van Gogh" you can generate images for the prompt "A portrait in the style of Van Gogh" and compare the erased and unerased models. We have also provided models with "cars" erased, and with "nudity" erased. You can also train and run your own custom model with a concept erased.')
57
 
58
  with gr.Row():
59
 
@@ -102,7 +102,7 @@ class Demo:
102
  with gr.Row():
103
 
104
  self.explain_train= gr.Markdown(interactive=False,
105
- value='In this part you can erase any concept from Stable Diffusion. Enter a prompt for the concept or style you want to erase, and select ESD-x if you want to focus erasure on prompts that mention the concept explicitly, or ESD-u if you want to erase the concept even for prompts that do not mention the concept. With default settings, it takes about 20 minutes to fine-tune the model; then you can try inference above or download the weights. The training code used here is slightly different than the code tested in the original paper. Code and details are at [github link](https://github.com/rohitgandikota/erasing).')
106
 
107
  with gr.Row():
108
 
 
53
  with gr.Row():
54
 
55
  self.explain_infr = gr.Markdown(interactive=False,
56
+ value='This is a demo of [Erasing Concepts from Stable Diffusion](https://erasing.baulab.info/). To try out a model where a concept has been erased, select a model and enter any prompt. For example, if you select the model "Van Gogh" you can generate images for the prompt "A portrait in the style of Van Gogh" and compare the erased and unerased models. We have also provided several other pre-fine-tuned models with artistic styles and objects erased (Check out the "ESD Model" drop-down). You can also train and run your own custom models. Check out the "train" section for custom erasure of concepts.')
57
 
58
  with gr.Row():
59
 
 
102
  with gr.Row():
103
 
104
  self.explain_train= gr.Markdown(interactive=False,
105
+ value='In this part you can erase any concept from Stable Diffusion. Enter a prompt for the concept or style you want to erase, and select ESD-x if you want to focus erasure on prompts that mention the concept explicitly. [NOTE: ESD-u is currently unavailable in this space. But you can duplicate the space and run it on GPU with VRAM >40GB for enabling ESD-u]. With default settings, it takes about 15 minutes to fine-tune the model; then you can try inference above or download the weights. The training code used here is slightly different than the code tested in the original paper. Code and details are at [github link](https://github.com/rohitgandikota/erasing).')
106
 
107
  with gr.Row():
108