Correct Music2Emo provenance and licensing

README.md

@@ -18,3 +18,6 @@ returns categorical mood tags together with valence and arousal estimates.
 The deployment uses the official Music2Emo checkpoint and the MERT-v1-95M
 backbone. The MERT weights are licensed under CC BY-NC 4.0, so this Space is
 for non-commercial use.
+
+Source attribution and third-party license details are recorded in
+`SOURCES.md` and `THIRD_PARTY_NOTICES.md`.

SOURCES.md

@@ -4,10 +4,12 @@
 
 - Paper: https://arxiv.org/abs/2502.03979
 - Source: https://github.com/AMAAI-Lab/Music2Emotion
-- Model files: https://huggingface.co/amaai-lab/music2emo
-- Pinned model revision:
+- Source license: MIT
+- Model repository: https://huggingface.co/amaai-lab/music2emo
+- Pinned model-repository revision:
   `b036e59471583c3d5b30c69e63e8c7323cc36c4a`
-- Code and Music2Emo checkpoint license: Apache-2.0
+- Model-repository metadata license: Apache-2.0
+- Checkpoint: `saved_models/J_all.ckpt`
 
 ## MERT
 
@@ -23,3 +25,5 @@ multitask checkpoint to produce 56 mood probabilities and valence-arousal
 scores. The Space downloads source modules and weights from the pinned
 Music2Emo revision at runtime instead of committing a copy of the upstream
 repository.
+
+See `THIRD_PARTY_NOTICES.md` for copyright and license notices.

THIRD_PARTY_NOTICES.md

@@ -0,0 +1,44 @@
+# Third-Party Notices
+
+## Music2Emo
+
+The inference adapter is based on the Music2Emo project:
+
+https://github.com/AMAAI-Lab/Music2Emotion
+
+MIT License
+
+Copyright (c) 2025 The Audio, Music, and AI (AMAAI) Lab
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+
+The released checkpoint and runtime assets are obtained from:
+
+https://huggingface.co/amaai-lab/music2emo
+
+That model repository is marked Apache-2.0 in its Hugging Face metadata.
+
+## MERT
+
+The deployment uses the MERT-v1-95M backbone:
+
+https://huggingface.co/m-a-p/MERT-v1-95M
+
+MERT-v1-95M is licensed under CC BY-NC 4.0. Its non-commercial restriction
+applies to this deployment.

app.py

@@ -21,9 +21,9 @@ except ImportError:
                     return self.func(*args, **kwargs)
                 return args[0]
 
-from music2emo_runtime import analyze_music
 from pyharp import ModelCard, build_endpoint
 
+from music2emo_runtime import analyze_music
 
 MIN_AUDIO_SECONDS = 1
 MAX_AUDIO_SECONDS = 60

model.json

@@ -1,12 +1,19 @@
 {
   "name": "Music2Emo",
   "task": "Music emotion recognition",
-  "source_repository": "AMAAI-Lab/Music2Emotion",
-  "source_revision": "b036e59471583c3d5b30c69e63e8c7323cc36c4a",
-  "source_license": "Apache-2.0",
+  "source": {
+    "repo": "AMAAI-Lab/Music2Emotion",
+    "license": "MIT"
+  },
+  "runtime_assets": {
+    "repo": "amaai-lab/music2emo",
+    "revision": "b036e59471583c3d5b30c69e63e8c7323cc36c4a",
+    "license": "Apache-2.0"
+  },
   "checkpoint": {
     "repo": "amaai-lab/music2emo",
     "file": "saved_models/J_all.ckpt",
+    "revision": "b036e59471583c3d5b30c69e63e8c7323cc36c4a",
     "license": "Apache-2.0"
   },
   "backbone": {

music2emo_runtime.py

@@ -10,13 +10,12 @@ import librosa
 import mir_eval
 import numpy as np
 import torch
-import torch.nn as nn
 import torchaudio
 from huggingface_hub import snapshot_download
 from music21 import note, stream
+from torch import nn
 from transformers import AutoModel, Wav2Vec2FeatureExtractor
 
-
 SOURCE_REPO = "amaai-lab/music2emo"
 SOURCE_REVISION = "b036e59471583c3d5b30c69e63e8c7323cc36c4a"
 MERT_REPO = "m-a-p/MERT-v1-95M"