use Flux2KleinPipeline + unpin transformers + klein-tuned defaults

app.py

@@ -3,7 +3,7 @@ import random
 import gradio as gr
 import torch
 import spaces
-from diffusers import Flux2Pipeline
+from diffusers import Flux2KleinPipeline
 
 BASE = "black-forest-labs/FLUX.2-klein-4B"
 LORA = "noema-art/impresstation-klein"
@@ -12,7 +12,7 @@ HF_TOKEN = os.environ.get("HF_TOKEN")
 MAX_SEED = 2**31 - 1
 
 dtype = torch.bfloat16
-pipe = Flux2Pipeline.from_pretrained(BASE, torch_dtype=dtype, token=HF_TOKEN)
+pipe = Flux2KleinPipeline.from_pretrained(BASE, torch_dtype=dtype, token=HF_TOKEN)
 pipe.load_lora_weights(LORA, adapter_name="impresstation", token=HF_TOKEN)
 pipe.to("cuda")
 
@@ -57,8 +57,8 @@ with gr.Blocks(css=CSS, title="ImpressStation — PS2-ify your image") as demo:
             inp = gr.Image(label="Your image", type="pil", height=360)
             extra = gr.Textbox(label="Describe / steer (optional)", placeholder="a determined young woman with red pigtails")
             with gr.Accordion("Settings", open=False):
-                steps = gr.Slider(8, 40, value=25, step=1, label="Steps")
-                guidance = gr.Slider(1.0, 8.0, value=4.0, step=0.1, label="Guidance")
+                steps = gr.Slider(4, 30, value=8, step=1, label="Steps")
+                guidance = gr.Slider(1.0, 6.0, value=2.5, step=0.1, label="Guidance")
                 seed = gr.Slider(0, MAX_SEED, value=42, step=1, label="Seed")
                 randomize = gr.Checkbox(value=True, label="Randomize seed")
             go = gr.Button("PS2-ify →", variant="primary")