Add RL model and curated examples

.gitattributes

@@ -33,3 +33,9 @@ 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
+assets/examples/blue_mug_1024.png filter=lfs diff=lfs merge=lfs -text
+assets/examples/blue_mug_1536.png filter=lfs diff=lfs merge=lfs -text
+assets/examples/desk_lamp_1024.png filter=lfs diff=lfs merge=lfs -text
+assets/examples/desk_lamp_1536.png filter=lfs diff=lfs merge=lfs -text
+assets/examples/red_apple_1024.png filter=lfs diff=lfs merge=lfs -text
+assets/examples/red_apple_1536.png filter=lfs diff=lfs merge=lfs -text

README.md

@@ -9,6 +9,7 @@ models:
   - SeFi-Image/SeFi-Image-1B-Base
   - SeFi-Image/SeFi-Image-2B-Base
   - SeFi-Image/SeFi-Image-5B-Base
+  - SeFi-Image/SeFi-Image-5B-RL
   - SeFi-Image/SeFi-Image-1B-turbo
   - SeFi-Image/SeFi-Image-2B-turbo
   - SeFi-Image/SeFi-Image-5B-turbo
@@ -16,19 +17,24 @@ models:
 
 # SeFi Image ZeroGPU
 
-Public Gradio ZeroGPU Space for SeFi-Image 1B, 2B, and 5B Base/Turbo checkpoints.
+Public Gradio ZeroGPU Space for SeFi-Image 1B, 2B, and 5B Base/RL/Turbo checkpoints.
 
 The model defaults match the SeFi model cards:
 
 | Family | Models | Steps | Guidance |
 | --- | --- | ---: | ---: |
 | Base | 1B, 2B, 5B | 50 | 4.0 |
+| RL | 5B | 50 | 4.0 |
 | Turbo | 1B, 2B, 5B | 4 | 1.0 |
 
 The SeFi checkpoints are gated under CC BY-NC 4.0. The Space uses an `HF_TOKEN`
 secret to download model files, so the Space owner account must first be approved
 for each selected SeFi model repository.
 
+The included examples were generated from this Space with `SeFi-Image-1B-turbo`
+at 1024x1024 and 1536x1536. Selecting an example fills the prompt, parameters,
+seed, and output image.
+
 The vendored `sefi/` inference package comes from
 `jmliu206/SeFi-Image` at commit `2f02744a187639ee41a296f8177cbbe7e5f333f5`
 and is covered by `LICENSE-SEFI-INFERENCE`.

app.py

@@ -10,7 +10,6 @@ from dataclasses import dataclass
 import gradio as gr
 import spaces
 import torch
-from huggingface_hub import hf_hub_download
 
 from sefi import SEFIInferencePipeline
 
@@ -55,6 +54,13 @@ MODEL_PRESETS: dict[str, ModelPreset] = {
         steps=50,
         guidance=4.0,
     ),
+    "5b-rl": ModelPreset(
+        label="SeFi-Image 5B RL",
+        repo_id="SeFi-Image/SeFi-Image-5B-RL",
+        family="rl",
+        steps=50,
+        guidance=4.0,
+    ),
     "1b-turbo": ModelPreset(
         label="SeFi-Image 1B Turbo",
         repo_id="SeFi-Image/SeFi-Image-1B-turbo",
@@ -80,21 +86,120 @@ MODEL_PRESETS: dict[str, ModelPreset] = {
 
 DEFAULT_MODEL = "1b-turbo"
 TURBO_STEPS = {4, 8, 10}
+EXAMPLES = [
+    {
+        "label": "Blue mug 1024",
+        "model_key": "1b-turbo",
+        "prompt": (
+            "A blue ceramic mug on a white desk, morning light, minimal clean "
+            "background, high detail product photo."
+        ),
+        "steps": 4,
+        "guidance": 1.0,
+        "width": 1024,
+        "height": 1024,
+        "seed": 6201,
+        "image": "assets/examples/blue_mug_1024.png",
+    },
+    {
+        "label": "Blue mug 1536",
+        "model_key": "1b-turbo",
+        "prompt": (
+            "A blue ceramic mug on a white desk, morning light, minimal clean "
+            "background, high detail product photo."
+        ),
+        "steps": 4,
+        "guidance": 1.0,
+        "width": 1536,
+        "height": 1536,
+        "seed": 6201,
+        "image": "assets/examples/blue_mug_1536.png",
+    },
+    {
+        "label": "Red apple 1024",
+        "model_key": "1b-turbo",
+        "prompt": (
+            "A red apple on a wooden table, soft natural window light, simple "
+            "product photograph, sharp focus."
+        ),
+        "steps": 4,
+        "guidance": 1.0,
+        "width": 1024,
+        "height": 1024,
+        "seed": 6202,
+        "image": "assets/examples/red_apple_1024.png",
+    },
+    {
+        "label": "Red apple 1536",
+        "model_key": "1b-turbo",
+        "prompt": (
+            "A red apple on a wooden table, soft natural window light, simple "
+            "product photograph, sharp focus."
+        ),
+        "steps": 4,
+        "guidance": 1.0,
+        "width": 1536,
+        "height": 1536,
+        "seed": 6202,
+        "image": "assets/examples/red_apple_1536.png",
+    },
+    {
+        "label": "Desk lamp 1024",
+        "model_key": "1b-turbo",
+        "prompt": (
+            "A modern brass desk lamp on a walnut writing table, warm evening "
+            "light, realistic product photography, uncluttered background."
+        ),
+        "steps": 4,
+        "guidance": 1.0,
+        "width": 1024,
+        "height": 1024,
+        "seed": 6203,
+        "image": "assets/examples/desk_lamp_1024.png",
+    },
+    {
+        "label": "Desk lamp 1536",
+        "model_key": "1b-turbo",
+        "prompt": (
+            "A modern brass desk lamp on a walnut writing table, warm evening "
+            "light, realistic product photography, uncluttered background."
+        ),
+        "steps": 4,
+        "guidance": 1.0,
+        "width": 1536,
+        "height": 1536,
+        "seed": 6203,
+        "image": "assets/examples/desk_lamp_1536.png",
+    },
+]
 
 _MODEL_LOCK = threading.Lock()
 _LOADED_MODEL_KEY: str | None = None
 _LOADED_PIPE: SEFIInferencePipeline | None = None
 
 
-def _hf_token() -> str | None:
-    token = os.getenv("HF_TOKEN")
-    return token.strip() if token and token.strip() else None
-
-
 def _model_choices() -> list[tuple[str, str]]:
     return [(preset.label, key) for key, preset in MODEL_PRESETS.items()]
 
 
+def _example_rows() -> list[list[str | int | float]]:
+    rows = []
+    for example in EXAMPLES:
+        preset = MODEL_PRESETS[str(example["model_key"])]
+        rows.append(
+            [
+                str(example["label"]),
+                preset.label,
+                str(example["prompt"]),
+                f'{example["width"]}x{example["height"]}',
+                int(example["steps"]),
+                float(example["guidance"]),
+                int(example["seed"]),
+            ]
+        )
+    return rows
+
+
 def _torch_cleanup() -> None:
     gc.collect()
     if torch.cuda.is_available():
@@ -161,19 +266,27 @@ def model_defaults(model_key: str):
     )
 
 
-def check_access(model_key: str) -> str:
-    preset = MODEL_PRESETS[model_key]
-    try:
-        hf_hub_download(
-            repo_id=preset.repo_id,
-            filename="sefi_config.yaml",
-            cache_dir=CACHE_DIR,
-            token=_hf_token(),
-        )
-    except Exception as exc:
-        return _friendly_error(exc, preset.repo_id)
-
-    return f"Access OK for `{preset.repo_id}`."
+def load_example(evt: gr.SelectData):
+    index = evt.index[0] if isinstance(evt.index, (list, tuple)) else evt.index
+    example = EXAMPLES[int(index)]
+    preset = MODEL_PRESETS[str(example["model_key"])]
+    status = (
+        f'Loaded example "{example["label"]}" generated with `{preset.repo_id}` '
+        f'at {example["width"]}x{example["height"]}, {example["steps"]} steps, '
+        f'guidance {example["guidance"]}, seed {example["seed"]}.'
+    )
+    return (
+        example["model_key"],
+        example["prompt"],
+        example["steps"],
+        example["guidance"],
+        example["width"],
+        example["height"],
+        example["seed"],
+        False,
+        example["image"],
+        status,
+    )
 
 
 def estimate_duration(
@@ -313,10 +426,9 @@ with gr.Blocks(title="SeFi Image ZeroGPU") as demo:
                     minimum=0,
                     maximum=2**31 - 1,
                 )
-                randomize_seed = gr.Checkbox(label="Randomize", value=False)
+                randomize_seed = gr.Checkbox(label="Randomize", value=True)
             with gr.Row():
                 run = gr.Button("Generate", variant="primary")
-                access = gr.Button("Check Access")
 
         with gr.Column(scale=1, min_width=360):
             image = gr.Image(label="Image", type="pil", format="png")
@@ -328,8 +440,35 @@ with gr.Blocks(title="SeFi Image ZeroGPU") as demo:
                 )
             )
 
+    examples = gr.Dataframe(
+        value=_example_rows(),
+        headers=["Example", "Model", "Prompt", "Size", "Steps", "Guidance", "Seed"],
+        datatype=["str", "str", "str", "str", "number", "number", "number"],
+        type="array",
+        label="Examples",
+        interactive=False,
+        wrap=True,
+        max_height=260,
+    )
+
     model.change(model_defaults, inputs=model, outputs=[steps, guidance, status])
-    access.click(check_access, inputs=model, outputs=status)
+    examples.select(
+        load_example,
+        outputs=[
+            model,
+            prompt,
+            steps,
+            guidance,
+            width,
+            height,
+            seed,
+            randomize_seed,
+            image,
+            status,
+        ],
+        api_name="load_example",
+        api_visibility="undocumented",
+    )
     run.click(
         generate,
         inputs=[