Update README.md

README.md

@@ -33,16 +33,22 @@ This is a LoRA derived from [stabilityai/stable-diffusion-3-medium-diffusers](ht
 The main validation prompt used during training was:
 
 ```
-a photo of a naked woman with large breasts
+a naked woman, front view, standing in a room. large breasts, pretty face, pussy. photo, RAW candid cinema, 16mm, color graded portra 400 film, remarkable color, ultra realistic, dry skin, shot with cinematic camera
+```
+
+Negative prompt:
+
+```
+ugly 3d render, deformed corpse, brushstrokes, painting
 ```
 
 ## Validation settings
-- CFG: `7.5`
+- CFG: `4.0`
 - CFG Rescale: `0.0`
-- Steps: `50`
+- Steps: `40`
 - Sampler: `euler`
-- Seed: `42`
-- Resolution: `1024`
+- Seed: `6`
+- Resolution: `816x1280`
 
 Note: The validation settings are not necessarily the same as the [training settings](#training-settings).
 
@@ -86,38 +92,3 @@ You may reuse the base model text encoder for inference.
 - Crop style: None
 - Crop aspect: None
 
-
-## Inference
-
-
-```python
-import torch
-from diffusers import DiffusionPipeline
-
-
-
-
-model_id = 'stabilityai/stable-diffusion-3-medium-diffusers'
-adapter_id = 'sdxl-training'
-prompt = 'a photo of a naked woman with large breasts'
-negative_prompt = 'blurry, cropped, ugly'
-pipeline = DiffusionPipeline.from_pretrained(model_id)\pipeline.load_adapter(adapter_id)
-pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu')
-
-prompt = "a photo of a naked woman with large breasts"
-negative_prompt = "blurry, cropped, ugly"
-
-pipeline = DiffusionPipeline.from_pretrained(model_id)
-pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu')
-image = pipeline(
-    prompt=prompt,
-    negative_prompt='blurry, cropped, ugly',
-    num_inference_steps=50,
-    generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(1641421826),
-    width=1152,
-    height=768,
-    guidance_scale=7.5,
-    guidance_rescale=0.0,
-).images[0]
-image.save("output.png", format="PNG")
-```