Model card auto-generated by SimpleTuner

README.md

@@ -10,47 +10,7 @@ tags:
   - lora
   - template:sd-lora
 inference: true
-widget:
-- text: 'unconditional (blank prompt)'
-  parameters:
-    negative_prompt: 'blurry, cropped, ugly'
-  output:
-    url: ./assets/image_0_0.png
-- text: 'transparent objects on a table in low light'
-  parameters:
-    negative_prompt: 'blurry, cropped, ugly'
-  output:
-    url: ./assets/image_1_0.png
-- text: 'transparent objects on a table in bright light'
-  parameters:
-    negative_prompt: 'blurry, cropped, ugly'
-  output:
-    url: ./assets/image_2_0.png
-- text: 'transparent objects on a table on a table in the backyard'
-  parameters:
-    negative_prompt: 'blurry, cropped, ugly'
-  output:
-    url: ./assets/image_3_0.png
-- text: 'partially filled transaprent objects on a table'
-  parameters:
-    negative_prompt: 'blurry, cropped, ugly'
-  output:
-    url: ./assets/image_4_0.png
-- text: 'transparent objects between opaque objects on a table'
-  parameters:
-    negative_prompt: 'blurry, cropped, ugly'
-  output:
-    url: ./assets/image_5_0.png
-- text: 'transparent syringes on a table'
-  parameters:
-    negative_prompt: 'blurry, cropped, ugly'
-  output:
-    url: ./assets/image_6_0.png
-- text: 'ethnographic photography of teddy bear at a picnic'
-  parameters:
-    negative_prompt: 'blurry, cropped, ugly'
-  output:
-    url: ./assets/image_7_0.png
+
 ---
 
 # simpletuner-lora-flux-v2
@@ -63,7 +23,7 @@ The main validation prompt used during training was:
 
 
 ```
-ethnographic photography of teddy bear at a picnic
+transparent objects on a table
 ```
 
 ## Validation settings
@@ -76,7 +36,7 @@ ethnographic photography of teddy bear at a picnic
 
 Note: The validation settings are not necessarily the same as the [training settings](#training-settings).
 
-You can find some example images in the following gallery:
+
 
 
 <Gallery />
@@ -88,7 +48,7 @@ You may reuse the base model text encoder for inference.
 ## Training settings
 
 - Training epochs: 0
-- Training steps: 39000
+- Training steps: 39100
 - Learning rate: 8e-05
 - Effective batch size: 4
   - Micro-batch size: 1
@@ -130,7 +90,7 @@ adapter_id = 'rohn132/simpletuner-lora-flux-v2'
 pipeline = DiffusionPipeline.from_pretrained(model_id)
 pipeline.load_lora_weights(adapter_id)
 
-prompt = "ethnographic photography of teddy bear at a picnic"
+prompt = "transparent objects on a table"
 
 pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu')
 image = pipeline(