sync from staging @ f46f7d67

README.md

@@ -1,12 +1,39 @@
 ---
-title: Colliderml Model Zoo Staging
-emoji: 🐨
-colorFrom: blue
+title: ColliderML Model Zoo
+emoji: 🦒
+colorFrom: green
 colorTo: blue
 sdk: gradio
-sdk_version: 6.11.0
+sdk_version: 4.44.0
 app_file: app.py
 pinned: false
+license: apache-2.0
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# ColliderML Model Zoo
+
+Browse models tagged `colliderml` on HuggingFace. Upload your own by
+adding the `colliderml` tag to your model card.
+
+## Curation
+
+Models are discovered automatically via
+`huggingface_hub.list_models(filter="colliderml")`. If you want your model
+shown here, add the following to your model card:
+
+```yaml
+---
+tags:
+- colliderml
+task_category: object-detection   # or whatever applies
+---
+```
+
+The zoo sorts by download count by default. You can also filter by task
+(`tracking`, `jets`, `anomaly`).
+
+## Deployment
+
+Synced automatically from `spaces/model-zoo/` on the
+[OpenDataDetector/ColliderML](https://github.com/OpenDataDetector/ColliderML)
+repo via the `sync-spaces.yml` workflow.

app.py

@@ -0,0 +1,77 @@
+"""
+ColliderML Model Zoo — Gradio HF Space.
+
+Thin browser over ``huggingface_hub.list_models(filter="colliderml")``.
+Sortable, filterable, with direct links to each model card.
+"""
+
+from __future__ import annotations
+
+import gradio as gr
+import pandas as pd
+from huggingface_hub import list_models
+
+
+def fetch_models(task_filter: str = "any") -> pd.DataFrame:
+    try:
+        models = list(list_models(filter="colliderml", limit=500, full=True))
+    except Exception as e:
+        return pd.DataFrame({"error": [str(e)]})
+
+    rows = []
+    for m in models:
+        tags = m.tags or []
+        task = next((t for t in tags if t in ("tracking", "jets", "anomaly")), "general")
+        if task_filter != "any" and task != task_filter:
+            continue
+        rows.append({
+            "model": m.modelId,
+            "task": task,
+            "downloads": getattr(m, "downloads", 0) or 0,
+            "likes": getattr(m, "likes", 0) or 0,
+            "pipeline": getattr(m, "pipeline_tag", "") or "",
+            "url": f"https://huggingface.co/{m.modelId}",
+        })
+
+    if not rows:
+        return pd.DataFrame(
+            {"info": ["No models tagged `colliderml` yet. Add the tag to your model card!"]}
+        )
+
+    df = pd.DataFrame(rows)
+    return df.sort_values("downloads", ascending=False).reset_index(drop=True)
+
+
+with gr.Blocks(
+    title="ColliderML Model Zoo",
+    theme=gr.themes.Soft(primary_hue="green"),
+) as demo:
+    gr.Markdown(
+        """
+        # 🦒 ColliderML Model Zoo
+
+        Models tagged `colliderml` on HuggingFace. Tag your own to appear here:
+
+        ```yaml
+        ---
+        tags:
+          - colliderml
+        ---
+        ```
+        """
+    )
+    with gr.Row():
+        task_filter = gr.Dropdown(
+            ["any", "tracking", "jets", "anomaly", "general"],
+            value="any",
+            label="Filter by task",
+        )
+        refresh_btn = gr.Button("Refresh")
+    table = gr.DataFrame(value=fetch_models())
+
+    refresh_btn.click(fetch_models, inputs=task_filter, outputs=table)
+    task_filter.change(fetch_models, inputs=task_filter, outputs=table)
+
+
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=7860)