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@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+examples/style_ref_01.png filter=lfs diff=lfs merge=lfs -text
+examples/style_ref_yeti.png filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,13 +1,40 @@
 ---
-title: Krea2 Style Reference
-emoji: 🐢
-colorFrom: blue
-colorTo: green
+title: Krea 2 Style Reference
+emoji: 🎨
+colorFrom: indigo
+colorTo: blue
 sdk: gradio
 sdk_version: 6.20.0
-python_version: '3.12'
 app_file: app.py
 pinned: false
+hardware: zero-a10g
+short_description: Style-guided image generation with Krea 2 Turbo
+python_version: "3.10"
+startup_duration_timeout: 600
+models:
+  - krea/Krea-2-Turbo
+  - ostris/krea2_turbo_style_reference
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Krea 2 Style Reference
+
+Generate an image from a text prompt, guided by a **style reference image**. This Space uses:
+
+- **Base model:** [krea/Krea-2-Turbo](https://huggingface.co/krea/Krea-2-Turbo) (8-step distilled Krea 2)
+- **LoRA:** [ostris/krea2_turbo_style_reference](https://huggingface.co/ostris/krea2_turbo_style_reference) (style reference conditioning)
+- **Pipeline:** [ostris/Krea2OstrisEdit](https://huggingface.co/ostris/Krea2OstrisEdit) (custom community pipeline for reference-image conditioning)
+
+## How it works
+
+Upload a style reference image and type a prompt describing what you want to generate. The LoRA conditions the Krea 2 Turbo model on both:
+1. **Text encoder** — the reference image is embedded into the prompt via Qwen3-VL vision placeholders
+2. **Latent space** — clean VAE latents of the reference are appended to the transformer sequence at flow time t=0
+
+This produces an image that follows your prompt while adopting the visual style of the reference image.
+
+## Inference recipe
+
+- **Steps:** 8 (Turbo distilled)
+- **Guidance:** 0.0 (disabled, per Krea 2 Turbo convention)
+- **LoRA scale:** 1.0 (adjustable)
+- **Resolution:** 1024×1024 (adjustable, must be multiples of 16)

app.py

@@ -0,0 +1,162 @@
+import spaces
+import torch
+import gradio as gr
+from diffusers import DiffusionPipeline
+
+BASE_MODEL = "krea/Krea-2-Turbo"
+LORA_REPO = "ostris/krea2_turbo_style_reference"
+LORA_WEIGHT = "krea2_style_reference.safetensors"
+CUSTOM_PIPELINE = "ostris/Krea2OstrisEdit"
+
+DTYPE = torch.bfloat16
+MAX_SEED = 2**31 - 1
+
+pipe = DiffusionPipeline.from_pretrained(
+    BASE_MODEL,
+    custom_pipeline=CUSTOM_PIPELINE,
+    torch_dtype=DTYPE,
+)
+pipe.to("cuda")
+pipe.load_lora_weights(LORA_REPO, weight_name=LORA_WEIGHT)
+
+
+@spaces.GPU(duration=90, size="large")
+def generate(
+    prompt,
+    style_ref_image,
+    lora_scale,
+    steps,
+    guidance,
+    width,
+    height,
+    seed,
+    randomize_seed,
+    progress=gr.Progress(track_tqdm=True),
+):
+    if not prompt or not prompt.strip():
+        raise gr.Error("Please enter a prompt.")
+    if style_ref_image is None:
+        raise gr.Error("Please upload a style reference image.")
+
+    if randomize_seed:
+        seed = torch.randint(0, MAX_SEED, (1,)).item()
+    seed = int(seed)
+
+    # Snap dimensions to multiples of 16 (vae_scale_factor * patch_size = 16)
+    multiple = 16
+    width = ((width + multiple - 1) // multiple) * multiple
+    height = ((height + multiple - 1) // multiple) * multiple
+
+    generator = torch.Generator("cuda").manual_seed(seed)
+
+    image = pipe(
+        prompt=prompt,
+        image=style_ref_image,
+        num_inference_steps=int(steps),
+        guidance_scale=float(guidance),
+        width=width,
+        height=height,
+        generator=generator,
+        attention_kwargs={"scale": float(lora_scale)},
+    ).images[0]
+
+    return image, seed
+
+
+CSS = """
+#page { max-width: 1100px; margin: 0 auto; padding: 4px 8px 32px; }
+#header { padding: 24px 4px 18px; border-bottom: 1px solid #e5e5e5; margin-bottom: 20px; }
+#header h1 { font-size: 32px; font-weight: 700; margin: 0 0 6px; letter-spacing: -0.02em; }
+#header .subtitle { font-size: 15px; color: #666; margin: 0; max-width: 70ch; line-height: 1.5; }
+#header .links { margin-top: 12px; display: flex; gap: 16px; }
+#header .links a {
+    font-size: 13px; color: #888; text-decoration: none;
+    border: 1px solid #ddd; border-radius: 6px; padding: 4px 10px;
+}
+#header .links a:hover { color: #333; border-color: #aaa; }
+footer { display: none !important; }
+"""
+
+HEADER = """
+<div id="header">
+  <h1>Krea 2 Style Reference</h1>
+  <p class="subtitle">
+    Generate an image from a text prompt, guided by a style reference image.
+    Powered by Krea&nbsp;2&nbsp;Turbo with the
+    <a href="https://huggingface.co/ostris/krea2_turbo_style_reference" target="_blank">Krea2 Style Reference LoRA</a>
+    and the
+    <a href="https://huggingface.co/ostris/Krea2OstrisEdit" target="_blank">Krea2OstrisEdit community pipeline</a>.
+  </p>
+  <div class="links">
+    <a href="https://huggingface.co/krea/Krea-2-Turbo" target="_blank">Base model ↗</a>
+    <a href="https://huggingface.co/ostris/krea2_turbo_style_reference" target="_blank">LoRA ↗</a>
+    <a href="https://github.com/ostris/ComfyUI-Krea2-Ostris-Edit" target="_blank">ComfyUI nodes ↗</a>
+  </div>
+</div>
+"""
+
+with gr.Blocks(title="Krea 2 Style Reference") as demo:
+    with gr.Column(elem_id="page"):
+        gr.HTML(HEADER)
+        with gr.Row(equal_height=False):
+            with gr.Column(scale=1):
+                prompt = gr.Textbox(
+                    label="Prompt",
+                    lines=3,
+                    placeholder="Describe what you want to generate, e.g. 'a white yeti with horns reading a book'",
+                )
+                style_ref = gr.Image(
+                    label="Style Reference Image",
+                    type="pil",
+                    height=300,
+                )
+                generate_btn = gr.Button("Generate", variant="primary", size="lg")
+                with gr.Accordion("Advanced", open=False):
+                    lora_scale = gr.Slider(
+                        0.0, 2.0, value=1.0, step=0.01,
+                        label="LoRA scale",
+                        info="Strength of the style reference influence",
+                    )
+                    steps = gr.Slider(1, 30, value=8, step=1, label="Steps")
+                    guidance = gr.Slider(
+                        0.0, 10.0, value=0.0, step=0.1,
+                        label="Guidance scale",
+                        info="Krea 2 Turbo uses 0.0 (guidance disabled)",
+                    )
+                    with gr.Row():
+                        width = gr.Slider(512, 1536, value=1024, step=16, label="Width")
+                        height = gr.Slider(512, 1536, value=1024, step=16, label="Height")
+                    with gr.Row():
+                        seed = gr.Slider(0, MAX_SEED, value=0, step=1, label="Seed")
+                        randomize_seed = gr.Checkbox(value=True, label="Randomize seed")
+            with gr.Column(scale=1):
+                result = gr.Image(label="Result", format="png", height=420)
+                used_seed = gr.Number(label="Seed used", visible=True, interactive=False)
+
+        gr.Examples(
+            examples=[
+                {
+                    "prompt": "a white yeti with horns reading a book",
+                    "style_ref_image": "examples/style_ref_yeti.png",
+                },
+                {
+                    "prompt": "a futuristic city skyline at sunset, cyberpunk aesthetic",
+                    "style_ref_image": "examples/style_ref_01.png",
+                },
+            ],
+            inputs=[prompt, style_ref],
+            outputs=[result, used_seed],
+            fn=generate,
+            cache_examples=True,
+            cache_mode="lazy",
+        )
+
+        inputs = [
+            prompt, style_ref, lora_scale, steps, guidance,
+            width, height, seed, randomize_seed,
+        ]
+        outputs = [result, used_seed]
+        gr.on([generate_btn.click, prompt.submit], generate, inputs, outputs)
+
+if __name__ == "__main__":
+    demo.launch(theme=gr.themes.Citrus(), css=CSS)

requirements.txt

@@ -0,0 +1,7 @@
+diffusers
+transformers
+accelerate
+peft
+safetensors
+torchvision
+sentencepiece