update ui

app.py

@@ -34,13 +34,12 @@ if(is_gpu_associated):
     # model_v1 = snapshot_download(repo_id="multimodalart/sd-fine-tunable")
     # model_v2 = snapshot_download(repo_id="stabilityai/stable-diffusion-2")
     # model_v2_512 = snapshot_download(repo_id="stabilityai/stable-diffusion-2-base")
-    model_alt = snapshot_download(repo_id="BAAI/AltDiffusion")
-    model_alt_m9 = snapshot_download(repo_id="BAAI/AltDiffusion-m9")
-    safety_checker = snapshot_download(repo_id="multimodalart/sd-sc")
-    model_to_load = model_alt_m9
-
-with zipfile.ZipFile("mix.zip", 'r') as zip_ref:
-    zip_ref.extractall(".")
+    # model_alt = snapshot_download(repo_id="BAAI/AltDiffusion")
+    # model_alt_m9 = snapshot_download(repo_id="BAAI/AltDiffusion-m9")
+    # safety_checker = snapshot_download(repo_id="multimodalart/sd-sc")
+    model_to_load = None # model_alt_m9
+# with zipfile.ZipFile("mix.zip", 'r') as zip_ref:
+#     zip_ref.extractall(".")
 
 def swap_text(option, base):
     resize_width = 768 if base == "v2-768" else 512
@@ -450,6 +449,27 @@ def checkbox_swap(checkbox):
     return [gr.update(visible=checkbox), gr.update(visible=checkbox), gr.update(visible=checkbox), gr.update(visible=checkbox)]
 
 with gr.Blocks(css=css) as demo:
+    gr.HTML(f'''
+        <div style="text-align: center; max-width: 650px; margin: 0 auto;">
+        <div
+        style="
+            display: inline-flex;
+            gap: 1.2rem;
+            font-size: 1.75rem;
+            margin-bottom: 10px;
+            width: 700px;
+            height: 100px;
+            margin: 0 auto;
+            /* border: 1px solid red; */
+            justify-content: center;
+        ">
+        <a href="https://github.com/FlagAI-Open/FlagAI"><img src="https://raw.githubusercontent.com/920232796/test/master/WechatIMG6906.png" alt="FlagAI" width="80%" height="80%" style="margin: 0 auto;"></a>
+        </div>
+            <p style="margin-bottom: 10px; font-size: 94%">
+        This is a dreambooth Training UI for <a href="https://huggingface.co/BAAI/AltDiffusion-m9" style="text-decoration: underline;">AltDiffusion-m9 model</a>,which is a multilingual image-to-text model supported 9 languages.
+        </p>
+        </div> 
+            ''')
     with gr.Box():
         if is_shared_ui:
             top_description = gr.HTML(f'''
@@ -482,12 +502,13 @@ with gr.Blocks(css=css) as demo:
                     <p>Do a <code>pip install requirements-local.txt</code></p> 
                     </div>
                 ''')
+
     gr.Markdown("# Dreambooth Training UI 💭")
-    gr.Markdown("Customize Stable Diffusion v1 or v2 (ⁿᵉʷ!) by giving it a few examples of a concept. Based on the [🧨 diffusers](https://github.com/huggingface/diffusers) implementation, additional techniques from [TheLastBen](https://github.com/TheLastBen/diffusers) and [ShivamShrirao](https://github.com/ShivamShrirao/diffusers)")
+    gr.Markdown("Customize AltDiffusion and AltDiffusion-m9(ⁿᵉʷ!) by giving it a few examples of a concept. Based on the [🧨 diffusers](https://github.com/huggingface/diffusers) implementation, additional techniques from [TheLastBen](https://github.com/TheLastBen/diffusers) and [ShivamShrirao](https://github.com/ShivamShrirao/diffusers)")
     
     with gr.Row() as what_are_you_training:
         type_of_thing = gr.Dropdown(label="What would you like to train?", choices=["object", "person", "style"], value="object", interactive=True)
-        base_model_to_use = gr.Dropdown(label="Which base model would you like to use?", choices=["v1-5", "v2-512", "v2-768", "alt", "alt_m9"], value="alt_m9", interactive=True)
+        base_model_to_use = gr.Dropdown(label="Which base model would you like to use?", choices=["alt", "alt_m9"], value="alt_m9", interactive=True)
     
     #Very hacky approach to emulate dynamically created Gradio components   
     with gr.Row() as upload_your_concept:

model.README.md

@@ -0,0 +1,24 @@
+---
+license: creativeml-openrail-m
+tags:
+- text-to-image
+widget:
+- text: sks
+---
+### test-m9 Dreambooth model trained by Alon77777 with [Hugging Face Dreambooth Training Space](https://huggingface.co/spaces/multimodalart/dreambooth-training) with the alt_m9 base model
+
+You run your new concept via `diffusers` [Colab Notebook for Inference](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_dreambooth_inference.ipynb). Don't forget to use the concept prompts! 
+
+Sample pictures of:
+  
+  
+  
+  
+  
+  
+  
+  
+  
+  
+sks (use that on your prompt) 
+![sks 0](https://huggingface.co/Alon77777/test-m9/resolve/main/concept_images/sks_%2810%29.jpg)![sks 1](https://huggingface.co/Alon77777/test-m9/resolve/main/concept_images/sks_%285%29.jpg)![sks 2](https://huggingface.co/Alon77777/test-m9/resolve/main/concept_images/sks_%282%29.jpg)![sks 3](https://huggingface.co/Alon77777/test-m9/resolve/main/concept_images/sks_%283%29.jpg)![sks 4](https://huggingface.co/Alon77777/test-m9/resolve/main/concept_images/sks_%2811%29.jpg)![sks 5](https://huggingface.co/Alon77777/test-m9/resolve/main/concept_images/sks_%288%29.jpg)![sks 6](https://huggingface.co/Alon77777/test-m9/resolve/main/concept_images/sks_%281%29.jpg)![sks 7](https://huggingface.co/Alon77777/test-m9/resolve/main/concept_images/sks_%289%29.jpg)![sks 8](https://huggingface.co/Alon77777/test-m9/resolve/main/concept_images/sks_%286%29.jpg)![sks 9](https://huggingface.co/Alon77777/test-m9/resolve/main/concept_images/sks_%284%29.jpg)![sks 10](https://huggingface.co/Alon77777/test-m9/resolve/main/concept_images/sks_%287%29.jpg)

token_identifier.txt

@@ -0,0 +1 @@
+sks

train_dreambooth.py

@@ -728,6 +728,8 @@ def run_training(args_imported):
         if args.train_text_encoder:
             text_encoder.train()
         for step, batch in enumerate(train_dataloader):
+            import pdb
+            pdb.set_trace()
             with accelerator.accumulate(unet):
                 # Convert images to latent space
                 with torch.no_grad():