[training scripts] add tags of diffusers-training (#7206)

* add tags for diffusers training

* add tags for diffusers training

* add tags for diffusers training

* add tags for diffusers training

* add tags for diffusers training

* add tags for diffusers training

* add dora tags for drambooth lora scripts

* style

examples/advanced_diffusion_training/train_dreambooth_lora_sd15_advanced.py

@@ -77,6 +77,7 @@ logger = get_logger(__name__)
 
 def save_model_card(
     repo_id: str,
+    use_dora: bool,
     images=None,
     base_model=str,
     train_text_encoder=False,
@@ -88,6 +89,7 @@ def save_model_card(
     vae_path=None,
 ):
     img_str = "widget:\n"
+    lora = "lora" if not use_dora else "dora"
     for i, image in enumerate(images):
         image.save(os.path.join(repo_folder, f"image_{i}.png"))
         img_str += f"""
@@ -139,9 +141,10 @@ to trigger concept `{key}` → use `{tokens}` in your prompt \n
 tags:
 - stable-diffusion
 - stable-diffusion-diffusers
+- diffusers-training
 - text-to-image
 - diffusers
-- lora
+- {lora}
 - template:sd-lora
 {img_str}
 base_model: {base_model}
@@ -1967,6 +1970,7 @@ def main(args):
 
         save_model_card(
             model_id if not args.push_to_hub else repo_id,
+            use_dora=args.use_dora,
             images=images,
             base_model=args.pretrained_model_name_or_path,
             train_text_encoder=args.train_text_encoder,

examples/advanced_diffusion_training/train_dreambooth_lora_sdxl_advanced.py

@@ -81,6 +81,7 @@ logger = get_logger(__name__)
 
 def save_model_card(
     repo_id: str,
+    use_dora: bool,
     images=None,
     base_model=str,
     train_text_encoder=False,
@@ -92,6 +93,7 @@ def save_model_card(
     vae_path=None,
 ):
     img_str = "widget:\n"
+    lora = "lora" if not use_dora else "dora"
     for i, image in enumerate(images):
         image.save(os.path.join(repo_folder, f"image_{i}.png"))
         img_str += f"""
@@ -144,9 +146,10 @@ to trigger concept `{key}` → use `{tokens}` in your prompt \n
 tags:
 - stable-diffusion-xl
 - stable-diffusion-xl-diffusers
+- diffusers-training
 - text-to-image
 - diffusers
-- lora
+- {lora}
 - template:sd-lora
 {img_str}
 base_model: {base_model}
@@ -2204,6 +2207,7 @@ def main(args):
 
         save_model_card(
             model_id if not args.push_to_hub else repo_id,
+            use_dora=args.use_dora,
             images=images,
             base_model=args.pretrained_model_name_or_path,
             train_text_encoder=args.train_text_encoder,

examples/controlnet/train_controlnet.py

@@ -242,6 +242,7 @@ These are controlnet weights trained on {base_model} with new type of conditioni
         "text-to-image",
         "diffusers",
         "controlnet",
+        "diffusers-training",
     ]
     model_card = populate_model_card(model_card, tags=tags)
 

examples/controlnet/train_controlnet_flax.py

@@ -169,6 +169,7 @@ These are controlnet weights trained on {base_model} with new type of conditioni
         "diffusers",
         "controlnet",
         "jax-diffusers-event",
+        "diffusers-training",
     ]
     model_card = populate_model_card(model_card, tags=tags)
 

examples/controlnet/train_controlnet_sdxl.py

@@ -243,6 +243,7 @@ These are controlnet weights trained on {base_model} with new type of conditioni
         "text-to-image",
         "diffusers",
         "controlnet",
+        "diffusers-training",
     ]
     model_card = populate_model_card(model_card, tags=tags)
 

examples/custom_diffusion/train_custom_diffusion.py

@@ -97,7 +97,14 @@ These are Custom Diffusion adaption weights for {base_model}. The weights were t
         inference=True,
     )
 
-    tags = ["text-to-image", "diffusers", "stable-diffusion", "stable-diffusion-diffusers", "custom-diffusion"]
+    tags = [
+        "text-to-image",
+        "diffusers",
+        "stable-diffusion",
+        "stable-diffusion-diffusers",
+        "custom-diffusion",
+        "diffusers-training",
+    ]
     model_card = populate_model_card(model_card, tags=tags)
 
     model_card.save(os.path.join(repo_folder, "README.md"))

examples/dreambooth/train_dreambooth.py

@@ -102,7 +102,7 @@ DreamBooth for the text encoder was enabled: {train_text_encoder}.
         inference=True,
     )
 
-    tags = ["text-to-image", "dreambooth"]
+    tags = ["text-to-image", "dreambooth", "diffusers-training"]
     if isinstance(pipeline, StableDiffusionPipeline):
         tags.extend(["stable-diffusion", "stable-diffusion-diffusers"])
     else:

examples/dreambooth/train_dreambooth_lora.py

@@ -106,7 +106,7 @@ LoRA for the text encoder was enabled: {train_text_encoder}.
         model_description=model_description,
         inference=True,
     )
-    tags = ["text-to-image", "diffusers", "lora"]
+    tags = ["text-to-image", "diffusers", "lora", "diffusers-training"]
     if isinstance(pipeline, StableDiffusionPipeline):
         tags.extend(["stable-diffusion", "stable-diffusion-diffusers"])
     else:

examples/dreambooth/train_dreambooth_lora_sdxl.py

@@ -96,6 +96,7 @@ def determine_scheduler_type(pretrained_model_name_or_path, revision):
 
 def save_model_card(
     repo_id: str,
+    use_dora: bool,
     images=None,
     base_model: str = None,
     train_text_encoder=False,
@@ -156,8 +157,9 @@ Please adhere to the licensing terms as described [here](https://huggingface.co/
     tags = [
         "text-to-image",
         "text-to-image",
+        "diffusers-training",
         "diffusers",
-        "lora",
+        "lora" if not use_dora else "dora",
         "template:sd-lora",
     ]
     if "playgroundai" in base_model:
@@ -1912,6 +1914,7 @@ def main(args):
         if args.push_to_hub:
             save_model_card(
                 repo_id,
+                use_dora=args.use_dora,
                 images=images,
                 base_model=args.pretrained_model_name_or_path,
                 train_text_encoder=args.train_text_encoder,

examples/kandinsky2_2/text_to_image/train_text_to_image_decoder.py

@@ -81,6 +81,7 @@ tags:
 - kandinsky
 - text-to-image
 - diffusers
+- diffusers-training
 inference: true
 ---
     """

examples/kandinsky2_2/text_to_image/train_text_to_image_lora_decoder.py

@@ -65,6 +65,7 @@ tags:
 - kandinsky
 - text-to-image
 - diffusers
+- diffusers-training
 - lora
 inference: true
 ---

examples/kandinsky2_2/text_to_image/train_text_to_image_lora_prior.py

@@ -65,6 +65,7 @@ tags:
 - kandinsky
 - text-to-image
 - diffusers
+- diffusers-training
 - lora
 inference: true
 ---

examples/kandinsky2_2/text_to_image/train_text_to_image_prior.py

@@ -82,6 +82,7 @@ tags:
 - kandinsky
 - text-to-image
 - diffusers
+- diffusers-training
 inference: true
 ---
     """

examples/research_projects/controlnet/train_controlnet_webdataset.py

@@ -460,6 +460,8 @@ tags:
 - text-to-image
 - diffusers
 - controlnet
+- diffusers-training
+- webdataset
 inference: true
 ---
     """

examples/research_projects/lora/train_text_to_image_lora.py

@@ -69,6 +69,7 @@ tags:
 - stable-diffusion-diffusers
 - text-to-image
 - diffusers
+- diffusers-training
 - lora
 inference: true
 ---

examples/research_projects/onnxruntime/textual_inversion/textual_inversion.py

@@ -100,6 +100,8 @@ tags:
 - text-to-image
 - diffusers
 - textual_inversion
+- diffusers-training
+- onxruntime
 inference: true
 ---
     """

examples/research_projects/realfill/train_realfill.py

@@ -87,6 +87,7 @@ tags:
 - text-to-image
 - diffusers
 - realfill
+- diffusers-training
 inference: true
 ---
     """

examples/t2i_adapter/train_t2i_adapter_sdxl.py

@@ -225,7 +225,14 @@ These are t2iadapter weights trained on {base_model} with new type of conditioni
         inference=True,
     )
 
-    tags = ["stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "diffusers", "t2iadapter"]
+    tags = [
+        "stable-diffusion-xl",
+        "stable-diffusion-xl-diffusers",
+        "text-to-image",
+        "diffusers",
+        "t2iadapter",
+        "diffusers-training",
+    ]
     model_card = populate_model_card(model_card, tags=tags)
 
     model_card.save(os.path.join(repo_folder, "README.md"))

examples/text_to_image/train_text_to_image.py

@@ -131,7 +131,7 @@ More information on all the CLI arguments and the environment are available on y
         inference=True,
     )
 
-    tags = ["stable-diffusion", "stable-diffusion-diffusers", "text-to-image", "diffusers"]
+    tags = ["stable-diffusion", "stable-diffusion-diffusers", "text-to-image", "diffusers", "diffusers-training"]
     model_card = populate_model_card(model_card, tags=tags)
 
     model_card.save(os.path.join(repo_folder, "README.md"))

examples/text_to_image/train_text_to_image_lora.py

@@ -90,6 +90,7 @@ These are LoRA adaption weights for {base_model}. The weights were fine-tuned on
         "stable-diffusion-diffusers",
         "text-to-image",
         "diffusers",
+        "diffusers-training",
         "lora",
     ]
     model_card = populate_model_card(model_card, tags=tags)