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README.md

@@ -1,13 +1,26 @@
 ---
-title: Krea2 Moody Golden Hour
-emoji: 📊
-colorFrom: pink
+title: Krea 2 Moody Golden Hour Editorial
+emoji: 🌅
+colorFrom: red
 colorTo: blue
 sdk: gradio
 sdk_version: 6.19.0
-python_version: '3.12'
 app_file: app.py
 pinned: false
+hardware: zero-a10g
+short_description: Krea-2 Turbo LoRA for moody golden-hour editorial images
+python_version: "3.10"
+models:
+  - krea/Krea-2-Turbo
+  - ilkerzgi/krea-2-moody-golden-hour-editorial-lora
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Krea 2 · Moody Golden Hour Editorial
+
+A Gradio demo for the [**Moody Golden Hour Editorial**](https://huggingface.co/ilkerzgi/krea-2-moody-golden-hour-editorial-lora)
+style LoRA, running on [**Krea-2-Turbo**](https://huggingface.co/krea/Krea-2-Turbo).
+
+The trigger phrase *"moody golden hour editorial style"* is automatically appended to every
+prompt. Just describe your scene and click Generate.
+
+**Recipe:** 8 steps, guidance_scale = 0.0 (Turbo), LoRA scale 1.0 (adjustable up to 1.25).

app.py

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+import random
+
+import gradio as gr
+import spaces
+import torch
+from diffusers import Krea2Pipeline
+
+# ---------------------------------------------------------------------------
+# Constants
+# ---------------------------------------------------------------------------
+BASE_MODEL = "krea/Krea-2-Turbo"
+LORA_REPO = "ilkerzgi/krea-2-moody-golden-hour-editorial-lora"
+LORA_WEIGHT_NAME = "moody-golden-hour-editorial.safetensors"
+TRIGGER_WORD = "moody golden hour editorial style"
+MAX_SEED = 2**31 - 1
+
+# Resolution presets — all multiples of 16 (Krea 2 requirement).
+RESOLUTIONS = {
+    "Square · 1024×1024": (1024, 1024),
+    "Portrait · 832×1216": (832, 1216),
+    "Landscape · 1216×832": (1216, 832),
+    "Tall · 1024×1280": (1024, 1280),
+}
+
+# Example prompts — drawn from the LoRA's own model-card example and
+# extended with subjects that showcase the moody golden-hour editorial style.
+EXAMPLES = [
+    "a lighthouse on a rocky cliff",
+    "a lone figure walking through a misty forest path",
+    "a vintage car parked on a desert highway at dusk",
+    "a fashion model leaning against a brick wall in soft warm light",
+]
+
+# ---------------------------------------------------------------------------
+# Model loading — at module scope, on CUDA (ZeroGPU CUDA emulation).
+# Krea 2 LoRAs load via the transformer's adapter API, per the official cards.
+# ---------------------------------------------------------------------------
+pipe = Krea2Pipeline.from_pretrained(BASE_MODEL, torch_dtype=torch.bfloat16)
+pipe.to("cuda")
+pipe.transformer.load_lora_adapter(LORA_REPO, weight_name=LORA_WEIGHT_NAME)
+pipe.transformer.set_adapters("default", weights=1.0)
+
+
+def _build_prompt(user_prompt: str) -> str:
+    """Prepend the trigger phrase so the user doesn't have to."""
+    p = user_prompt.strip()
+    if not p:
+        return p
+    if TRIGGER_WORD.lower() in p.lower():
+        return p
+    return f"{p}. {TRIGGER_WORD}"
+
+
+@spaces.GPU(duration=60)
+def generate(
+    prompt,
+    resolution_label,
+    lora_scale,
+    seed,
+    randomize_seed,
+    progress=gr.Progress(track_tqdm=True),
+):
+    if not prompt or not prompt.strip():
+        raise gr.Error("Enter a prompt to generate an image.")
+
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+    seed = int(seed)
+
+    width, height = RESOLUTIONS[resolution_label]
+
+    # Apply the LoRA scale dynamically.
+    pipe.transformer.set_adapters("default", weights=float(lora_scale))
+
+    full_prompt = _build_prompt(prompt)
+
+    generator = torch.Generator("cuda").manual_seed(seed)
+    image = pipe(
+        prompt=full_prompt,
+        num_inference_steps=8,
+        guidance_scale=0.0,
+        width=width,
+        height=height,
+        generator=generator,
+    ).images[0]
+
+    return image, seed
+
+
+# ---------------------------------------------------------------------------
+# UI
+# ---------------------------------------------------------------------------
+with gr.Blocks(title="Krea 2 · Moody Golden Hour Editorial") as demo:
+    gr.Markdown(
+        """
+        # Krea 2 · Moody Golden Hour Editorial
+
+        A style LoRA for [**Krea-2-Turbo**](https://huggingface.co/krea/Krea-2-Turbo) by
+        [**ilkerzgi**](https://huggingface.co/ilkerzgi). Generates moody, warm, golden-hour
+        editorial imagery. The trigger phrase *\"moody golden hour editorial style\"* is
+        auto-appended to your prompt.
+        """
+    )
+
+    with gr.Row(equal_height=True):
+        with gr.Column(scale=5):
+            prompt = gr.Textbox(
+                label="Prompt",
+                lines=3,
+                placeholder="Describe your scene… e.g. a lighthouse on a rocky cliff",
+                autofocus=True,
+            )
+            resolution = gr.Radio(
+                choices=list(RESOLUTIONS.keys()),
+                value="Square · 1024×1024",
+                label="Aspect ratio",
+            )
+            run_button = gr.Button("Generate", variant="primary", size="lg")
+
+            with gr.Accordion("Advanced", open=False):
+                lora_scale = gr.Slider(
+                    label="LoRA scale (style strength)",
+                    minimum=0.0,
+                    maximum=1.5,
+                    step=0.05,
+                    value=1.0,
+                    info="1.0 = default, up to 1.25 for a stronger look.",
+                )
+                with gr.Row():
+                    seed = gr.Slider(
+                        label="Seed",
+                        minimum=0,
+                        maximum=MAX_SEED,
+                        step=1,
+                        value=0,
+                    )
+                    randomize_seed = gr.Checkbox(
+                        label="Randomize seed", value=True
+                    )
+
+        with gr.Column(scale=5):
+            result = gr.Image(label="Result", format="png", show_label=False)
+
+    gr.Examples(
+        fn=generate,
+        examples=EXAMPLES,
+        inputs=[prompt],
+        outputs=[result, seed],
+        cache_examples=True,
+        cache_mode="lazy",
+    )
+
+    gr.on(
+        triggers=[run_button.click, prompt.submit],
+        fn=generate,
+        inputs=[prompt, resolution, lora_scale, seed, randomize_seed],
+        outputs=[result, seed],
+    )
+
+if __name__ == "__main__":
+    demo.launch(show_error=True)

requirements.txt

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+git+https://github.com/huggingface/diffusers.git
+transformers>=4.57.0
+accelerate
+sentencepiece
+torchvision
+safetensors
+peft