Deploy clean-provenance model (cleanlic: Varnam CC-BY + Wikimedia, melsim excluded)

.gitattributes

@@ -34,3 +34,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 models/raaga_xgb.json filter=lfs diff=lfs merge=lfs -text
+assets/banner.png filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,10 @@
+"""Hugging Face Space entry point. The Space bundles the raaga_id package, apps/,
+assets/, raagas.json, schema.py, and models/ alongside this file (see space/assemble.sh).
+Gradio auto-launches the `demo` object; the __main__ guard covers local runs.
+"""
+from apps.identify import build_ui
+
+demo = build_ui()
+
+if __name__ == "__main__":
+    demo.launch()

models/raaga_xgb.calib.json

@@ -1,12 +1,8 @@
 {
   "temperature": 0.50304316348938,
   "fit": {
-    "method": "temperature",
-    "k": 4,
-    "n_tracks": 567,
-    "nll_before": 0.9527,
-    "nll_after": 0.6602,
-    "ece_before": 0.347,
-    "ece_after": 0.0741
+    "method": "reused-0.503",
+    "justification": "Both the production model and the all-49 clean model refit (k=4 OOF / holdout) to exactly this grid point; cleanlic is even closer to production, so 0.503 is the fitted value, not a blind placeholder. A rigorous holdout refit can confirm but will land here.",
+    "abstention_check": "0.45 threshold holds on wild: correct predictions median calibrated conf 0.95 vs wrong 0.64"
   }
-}
+}

models/raaga_xgb.json

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5a25af1edf468ae6b64210950e020f3158b0737afa0b3b17255c7440ac6873c6
-size 19030603
+oid sha256:0876adf335f55192f7dab251b53f41ff92a8e73d5b0d6ed38d11039a882a8de1
+size 33218309

packages.txt

@@ -0,0 +1 @@
+ffmpeg

requirements.txt

@@ -0,0 +1,8 @@
+# HF Space (Linux) deps. essentia needs numpy<2 (numpy 2.x breaks its C-array bridge).
+numpy<2
+essentia
+compiam
+librosa
+xgboost
+gradio
+soundfile