add curated set of HuggingFace diffusers models for 2.3.1 release

- Final list can be found in invokeai/configs/INITIAL_MODELS.yaml

- After installing all the models, I discovered a bug in the file
  selection form that caused a crash when no remaining uninstalled
  models remained. So had to fix this.

invokeai/configs/INITIAL_MODELS.yaml

@@ -6,53 +6,78 @@ stable-diffusion-1.5:
      repo_id: stabilityai/sd-vae-ft-mse
    recommended: True
    default: True
-inpainting-1.5:
+sd-inpainting-1.5:
   description: RunwayML SD 1.5 model optimized for inpainting, diffusers version (4.27 GB)
   repo_id: runwayml/stable-diffusion-inpainting
   format: diffusers
   vae:
     repo_id: stabilityai/sd-vae-ft-mse
   recommended: True
-dreamlike-diffusion-1.0:
+stable-diffusion-2.1:
-  description: An SD 1.5 model fine tuned on high quality art by dreamlike.art, diffusers version (2.13 BG)
-  format: diffusers
-  repo_id: dreamlike-art/dreamlike-diffusion-1.0
-  vae:
-     repo_id: stabilityai/sd-vae-ft-mse
-  recommended: True
-dreamlike-photoreal-2.0:
-  description: A photorealistic model trained on 768 pixel images based on SD 1.5 (2.13 GB)
-  format: diffusers
-  repo_id: dreamlike-art/dreamlike-photoreal-2.0
-  recommended: False
-stable-diffusion-2.1-768:
    description: Stable Diffusion version 2.1 diffusers model, trained on 768 pixel images (5.21 GB)
    repo_id: stabilityai/stable-diffusion-2-1
    format: diffusers
    recommended: True
-stable-diffusion-2.1-base:
+sd-inpainting-2.0:
-   description: Stable Diffusion version 2.1 diffusers base model, trained on 512 pixel images (5.21 GB)
+   description: Stable Diffusion version 2.0 inpainting model (5.21 GB)
-   repo_id: stabilityai/stable-diffusion-2-1-base
+   repo_id: stabilityai/stable-diffusion-2-1
    format: diffusers
    recommended: False
+analog-diffusion-1.0:
+   description: An SD-1.5 model trained on diverse analog photographs (2.13 GB)
+   repo_id: wavymulder/Analog-Diffusion
+   format: diffusers
+   recommended: false
+deliberate-1.0:
+   description: Versatile model that produces detailed images up to 768px (4.27 GB)
+   format: diffusers
+   repo_id: XpucT/Deliberate
+   recommended: False
+d&d-diffusion-1.0:
+   description: Dungeons & Dragons characters (2.13 GB)
+   format: diffusers
+   repo_id: 0xJustin/Dungeons-and-Diffusion
+   recommended: False
+dreamlike-photoreal-2.0:
+   description: A photorealistic model trained on 768 pixel images based on SD 1.5 (2.13 GB)
+   format: diffusers
+   repo_id: dreamlike-art/dreamlike-photoreal-2.0
+   recommended: False
+inkpunk-1.0:
+   description: Stylized illustrations inspired by Gorillaz, FLCL and Shinkawa; prompt with "nvinkpunk" (4.27 GB)
+   format: diffusers
+   repo_id: Envvi/Inkpunk-Diffusion
+   recommended: False
 openjourney-4.0:
-  description: An SD 1.5 model fine tuned on Midjourney images by PromptHero - include "mdjrny-v4 style" in your prompts (2.13 GB)
+   description: An SD 1.5 model fine tuned on Midjourney; prompt with "mdjrny-v4 style" (2.13 GB)
-  format: diffusers
+   format: diffusers
-  repo_id: prompthero/openjourney
+   repo_id: prompthero/openjourney
-  vae:
+   vae:
      repo_id: stabilityai/sd-vae-ft-mse
-  recommended: False
+   recommended: False
-nitro-diffusion-1.0:
+portrait-plus-1.0:
-   description: A SD 1.5 model trained on three artstyles - prompt with "archer style", "arcane style" and/or "modern disney style" (2.13 GB)
+   description: An SD-1.5 model trained on close range portraits of people; prompt with "portrait+" (2.13 GB)
-   repo_id: nitrosocke/Nitro-Diffusion
+   format: diffusers
+   repo_id: wavymulder/portraitplus
+   recommended: False
+seek-art-mega-1.0:
+   description: A general use SD-1.5 "anything" model that supports multiple styles (2.1 GB)
+   repo_id: coreco/seek.art_MEGA
    format: diffusers
    vae:
      repo_id: stabilityai/sd-vae-ft-mse
    recommended: False
 trinart-2.0:
-   description: An SD model finetuned with ~40,000 assorted high resolution manga/anime-style pictures, diffusers version (2.13 GB)
+   description: An SD-1.5 model finetuned with ~40K assorted high resolution manga/anime-style images (2.13 GB)
    repo_id: naclbit/trinart_stable_diffusion_v2
    format: diffusers
    vae:
      repo_id: stabilityai/sd-vae-ft-mse
    recommended: False
+waifu-diffusion-1.4:
+   description: An SD-1.5 model trained on 680k anime/manga-style images (2.13 GB)
+   repo_id: hakurei/waifu-diffusion
+   format: diffusers
+   vae:
+     repo_id: stabilityai/sd-vae-ft-mse
+   recommended: False

ldm/invoke/config/model_install.py

@@ -114,37 +114,37 @@ class addModelsForm(npyscreen.FormMultiPage):
                 relx=4,
             )
         self.nextrely += 1
-        self.add_widget_intelligent(
+        if len(self.starter_model_list) > 0:
-            CenteredTitleText,
+            self.add_widget_intelligent(
-            name="== STARTER MODELS (recommended ones selected) ==",
+                CenteredTitleText,
-            editable=False,
+                name="== STARTER MODELS (recommended ones selected) ==",
-            color="CONTROL",
+                editable=False,
-        )
+                color="CONTROL",
-        self.nextrely -= 1
+            )
-        self.add_widget_intelligent(
+            self.nextrely -= 1
-            CenteredTitleText,
+            self.add_widget_intelligent(
-            name="Select from a starter set of Stable Diffusion models from HuggingFace:",
+                CenteredTitleText,
-            editable=False,
+                name="Select from a starter set of Stable Diffusion models from HuggingFace.",
-            labelColor="CAUTION",
+                editable=False,
-        )
+                labelColor="CAUTION",
-
+            )
-        self.nextrely -= 1
+            self.nextrely -= 1
-        # if user has already installed some initial models, then don't patronize them
+            # if user has already installed some initial models, then don't patronize them
-        # by showing more recommendations
+            # by showing more recommendations
-        show_recommended = not self.existing_models
+            show_recommended = not self.existing_models
-        self.models_selected = self.add_widget_intelligent(
+            self.models_selected = self.add_widget_intelligent(
-            npyscreen.MultiSelect,
+                npyscreen.MultiSelect,
-            name="Install Starter Models",
+                name="Install Starter Models",
-            values=starter_model_labels,
+                values=starter_model_labels,
-            value=[
+                value=[
-                self.starter_model_list.index(x)
+                    self.starter_model_list.index(x)
-                for x in self.starter_model_list
+                    for x in self.starter_model_list
-                if show_recommended and x in recommended_models
+                    if show_recommended and x in recommended_models
-            ],
+                ],
-            max_height=len(starter_model_labels) + 1,
+                max_height=len(starter_model_labels) + 1,
-            relx=4,
+                relx=4,
-            scroll_exit=True,
+                scroll_exit=True,
-        )
+            )
         self.add_widget_intelligent(
             CenteredTitleText,
             name='== IMPORT LOCAL AND REMOTE MODELS ==',
@@ -166,7 +166,11 @@ class addModelsForm(npyscreen.FormMultiPage):
             )
             self.nextrely -= 1
         self.import_model_paths = self.add_widget_intelligent(
-            TextBox, max_height=5, scroll_exit=True, editable=True, relx=4
+            TextBox,
+            max_height=7,
+            scroll_exit=True,
+            editable=True,
+            relx=4
         )
         self.nextrely += 1
         self.show_directory_fields = self.add_widget_intelligent(
@@ -241,7 +245,8 @@ class addModelsForm(npyscreen.FormMultiPage):
 
     def resize(self):
         super().resize()
-        self.models_selected.values = self._get_starter_model_labels()
+        if hasattr(self,'models_selected'):
+            self.models_selected.values = self._get_starter_model_labels()
 
     def _clear_scan_directory(self):
         if not self.show_directory_fields.value:
@@ -320,11 +325,14 @@ class addModelsForm(npyscreen.FormMultiPage):
         selections = self.parentApp.user_selections
 
         # starter models to install/remove
-        starter_models = dict(
+        if hasattr(self,'models_selected'):
-            map(
+            starter_models = dict(
-                lambda x: (self.starter_model_list[x], True), self.models_selected.value
+                map(
+                    lambda x: (self.starter_model_list[x], True), self.models_selected.value
+                )
             )
-        )
+        else:
+            starter_models = dict()
         selections.purge_deleted_models = False
         if hasattr(self, "previously_installed_models"):
             unchecked = [