Feature Extraction
Transformers
Safetensors
sheetsage2
audio
music
music-transcription
midi
abc-notation
custom_code
Instructions to use m-a-p/SheetSage2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m-a-p/SheetSage2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="m-a-p/SheetSage2", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("m-a-p/SheetSage2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "scores": [ | |
| { | |
| "task": "beat", | |
| "dataset": "GTZAN", | |
| "metric": "F1", | |
| "score": 86.27, | |
| "settings": { | |
| "preset": "paper", | |
| "sample_rate": 24000, | |
| "window_seconds": 300, | |
| "overlap_seconds": 100, | |
| "lookahead_seconds": 0, | |
| "max_length": 5120, | |
| "decoding": "greedy", | |
| "attention": "sdpa", | |
| "weight_dtype": "float32", | |
| "autocast_dtype": "bfloat16", | |
| "batch_size": 1, | |
| "prompts": [ | |
| "timestamp", | |
| "downbeat_meter", | |
| "key" | |
| ], | |
| "device": "NVIDIA H800", | |
| "cuda_version": "12.6" | |
| }, | |
| "evaluation": { | |
| "num_tracks": 999, | |
| "matching_tolerance_seconds": 0.07, | |
| "min_event_time_seconds": 5.0, | |
| "trim_reference_and_predictions": true, | |
| "aggregation": "macro_average_per_track_f1" | |
| } | |
| }, | |
| { | |
| "task": "beat", | |
| "dataset": "osu2017", | |
| "metric": "F1", | |
| "score": 93.01, | |
| "settings": { | |
| "preset": "paper", | |
| "sample_rate": 24000, | |
| "window_seconds": 300, | |
| "overlap_seconds": 100, | |
| "lookahead_seconds": 0, | |
| "max_length": 5120, | |
| "decoding": "greedy", | |
| "attention": "sdpa", | |
| "weight_dtype": "float32", | |
| "autocast_dtype": "bfloat16", | |
| "batch_size": 1, | |
| "prompts": [ | |
| "timestamp", | |
| "downbeat_meter", | |
| "key", | |
| "chord_full" | |
| ], | |
| "device": "NVIDIA H800", | |
| "cuda_version": "12.6" | |
| }, | |
| "evaluation": { | |
| "num_tracks": 142, | |
| "matching_tolerance_seconds": 0.07, | |
| "min_event_time_seconds": 5.0, | |
| "trim_reference_and_predictions": true, | |
| "aggregation": "macro_average_per_track_f1" | |
| } | |
| }, | |
| { | |
| "task": "downbeat", | |
| "dataset": "GTZAN", | |
| "metric": "F1", | |
| "score": 80.45, | |
| "settings": { | |
| "preset": "paper", | |
| "sample_rate": 24000, | |
| "window_seconds": 300, | |
| "overlap_seconds": 100, | |
| "lookahead_seconds": 0, | |
| "max_length": 5120, | |
| "decoding": "greedy", | |
| "attention": "sdpa", | |
| "weight_dtype": "float32", | |
| "autocast_dtype": "bfloat16", | |
| "batch_size": 1, | |
| "prompts": [ | |
| "timestamp", | |
| "downbeat_meter", | |
| "key" | |
| ], | |
| "device": "NVIDIA H800", | |
| "cuda_version": "12.6" | |
| }, | |
| "evaluation": { | |
| "num_tracks": 993, | |
| "matching_tolerance_seconds": 0.07, | |
| "min_event_time_seconds": 5.0, | |
| "trim_reference_and_predictions": true, | |
| "aggregation": "macro_average_per_track_f1" | |
| } | |
| }, | |
| { | |
| "task": "downbeat", | |
| "dataset": "osu2017", | |
| "metric": "F1", | |
| "score": 92.9, | |
| "settings": { | |
| "preset": "paper", | |
| "sample_rate": 24000, | |
| "window_seconds": 300, | |
| "overlap_seconds": 100, | |
| "lookahead_seconds": 0, | |
| "max_length": 5120, | |
| "decoding": "greedy", | |
| "attention": "sdpa", | |
| "weight_dtype": "float32", | |
| "autocast_dtype": "bfloat16", | |
| "batch_size": 1, | |
| "prompts": [ | |
| "timestamp", | |
| "downbeat_meter", | |
| "key", | |
| "chord_full" | |
| ], | |
| "device": "NVIDIA H800", | |
| "cuda_version": "12.6" | |
| }, | |
| "evaluation": { | |
| "num_tracks": 142, | |
| "matching_tolerance_seconds": 0.07, | |
| "min_event_time_seconds": 5.0, | |
| "trim_reference_and_predictions": true, | |
| "aggregation": "macro_average_per_track_f1" | |
| } | |
| }, | |
| { | |
| "task": "key", | |
| "dataset": "GiantSteps", | |
| "metric": "weighted_accuracy", | |
| "score": 77.73, | |
| "settings": { | |
| "preset": "paper", | |
| "sample_rate": 24000, | |
| "window_seconds": 300, | |
| "overlap_seconds": 100, | |
| "lookahead_seconds": 0, | |
| "max_length": 5120, | |
| "decoding": "greedy", | |
| "attention": "sdpa", | |
| "weight_dtype": "float32", | |
| "autocast_dtype": "bfloat16", | |
| "batch_size": 1, | |
| "prompts": [ | |
| "timestamp", | |
| "downbeat_meter", | |
| "key" | |
| ], | |
| "device": "NVIDIA H800", | |
| "cuda_version": "12.6" | |
| } | |
| }, | |
| { | |
| "task": "key", | |
| "dataset": "GTZAN", | |
| "metric": "weighted_accuracy", | |
| "score": 75.77, | |
| "settings": { | |
| "preset": "paper", | |
| "sample_rate": 24000, | |
| "window_seconds": 300, | |
| "overlap_seconds": 100, | |
| "lookahead_seconds": 0, | |
| "max_length": 5120, | |
| "decoding": "greedy", | |
| "attention": "sdpa", | |
| "weight_dtype": "float32", | |
| "autocast_dtype": "bfloat16", | |
| "batch_size": 1, | |
| "prompts": [ | |
| "timestamp", | |
| "downbeat_meter", | |
| "key" | |
| ], | |
| "device": "NVIDIA H800", | |
| "cuda_version": "12.6" | |
| } | |
| }, | |
| { | |
| "task": "chord", | |
| "dataset": "osu2017", | |
| "metric": "majmin", | |
| "score": 90.08, | |
| "settings": { | |
| "preset": "paper", | |
| "sample_rate": 24000, | |
| "window_seconds": 300, | |
| "overlap_seconds": 100, | |
| "lookahead_seconds": 0, | |
| "max_length": 5120, | |
| "decoding": "greedy", | |
| "attention": "sdpa", | |
| "weight_dtype": "float32", | |
| "autocast_dtype": "bfloat16", | |
| "batch_size": 1, | |
| "prompts": [ | |
| "timestamp", | |
| "downbeat_meter", | |
| "key", | |
| "chord_full" | |
| ], | |
| "device": "NVIDIA H800", | |
| "cuda_version": "12.6" | |
| } | |
| }, | |
| { | |
| "task": "chord", | |
| "dataset": "Chords1217", | |
| "metric": "majmin", | |
| "score": 83.81, | |
| "settings": { | |
| "preset": "paper", | |
| "sample_rate": 24000, | |
| "window_seconds": 300, | |
| "overlap_seconds": 100, | |
| "lookahead_seconds": 0, | |
| "max_length": 5120, | |
| "decoding": "greedy", | |
| "attention": "sdpa", | |
| "weight_dtype": "float32", | |
| "autocast_dtype": "bfloat16", | |
| "batch_size": 1, | |
| "prompts": [ | |
| "timestamp", | |
| "downbeat_meter", | |
| "chord_full" | |
| ], | |
| "device": "NVIDIA H800", | |
| "cuda_version": "12.6" | |
| } | |
| }, | |
| { | |
| "task": "chord", | |
| "dataset": "JAAH", | |
| "metric": "majmin", | |
| "score": 64.5, | |
| "settings": { | |
| "preset": "paper", | |
| "sample_rate": 24000, | |
| "window_seconds": 300, | |
| "overlap_seconds": 100, | |
| "lookahead_seconds": 0, | |
| "max_length": 5120, | |
| "decoding": "greedy", | |
| "attention": "sdpa", | |
| "weight_dtype": "float32", | |
| "autocast_dtype": "bfloat16", | |
| "batch_size": 1, | |
| "prompts": [ | |
| "timestamp", | |
| "downbeat_meter", | |
| "chord_full" | |
| ], | |
| "cuda_version": "12.6" | |
| }, | |
| "score_unrounded": 64.50302704985715, | |
| "num_tracks": 113, | |
| "source": "benchmarks/jaah_results.json", | |
| "evaluation": { | |
| "reference": "official_annotations_intersected_with_audio_span", | |
| "aggregation": "reference_span_weighted_mean_per_track_mir_eval_majmin", | |
| "eligible_reference_percent": 93.87347199893611, | |
| "ci95_percent": [ | |
| 61.02541843882439, | |
| 67.64783306565447 | |
| ] | |
| } | |
| }, | |
| { | |
| "task": "structure", | |
| "dataset": "HarmonixSet", | |
| "metric": "accuracy", | |
| "score": 80.51, | |
| "settings": { | |
| "preset": "paper", | |
| "sample_rate": 24000, | |
| "window_seconds": 300, | |
| "overlap_seconds": 100, | |
| "lookahead_seconds": 0, | |
| "max_length": 5120, | |
| "decoding": "greedy", | |
| "attention": "sdpa", | |
| "weight_dtype": "float32", | |
| "autocast_dtype": "bfloat16", | |
| "batch_size": 1, | |
| "prompts": [ | |
| "timestamp", | |
| "downbeat_meter", | |
| "structure" | |
| ], | |
| "device": "NVIDIA H800", | |
| "cuda_version": "12.6" | |
| } | |
| }, | |
| { | |
| "task": "structure", | |
| "dataset": "HarmonixSet", | |
| "metric": "F1@0.5s", | |
| "score": 67.96, | |
| "settings": { | |
| "preset": "paper", | |
| "sample_rate": 24000, | |
| "window_seconds": 300, | |
| "overlap_seconds": 100, | |
| "lookahead_seconds": 0, | |
| "max_length": 5120, | |
| "decoding": "greedy", | |
| "attention": "sdpa", | |
| "weight_dtype": "float32", | |
| "autocast_dtype": "bfloat16", | |
| "batch_size": 1, | |
| "prompts": [ | |
| "timestamp", | |
| "downbeat_meter", | |
| "structure" | |
| ], | |
| "device": "NVIDIA H800", | |
| "cuda_version": "12.6" | |
| } | |
| }, | |
| { | |
| "task": "structure", | |
| "dataset": "HarmonixSet", | |
| "metric": "F1@3s", | |
| "score": 82.86, | |
| "settings": { | |
| "preset": "paper", | |
| "sample_rate": 24000, | |
| "window_seconds": 300, | |
| "overlap_seconds": 100, | |
| "lookahead_seconds": 0, | |
| "max_length": 5120, | |
| "decoding": "greedy", | |
| "attention": "sdpa", | |
| "weight_dtype": "float32", | |
| "autocast_dtype": "bfloat16", | |
| "batch_size": 1, | |
| "prompts": [ | |
| "timestamp", | |
| "downbeat_meter", | |
| "structure" | |
| ], | |
| "device": "NVIDIA H800", | |
| "cuda_version": "12.6" | |
| } | |
| }, | |
| { | |
| "task": "melody", | |
| "dataset": "RWC-Pop", | |
| "metric": "vocal_pitch_class_F1", | |
| "score": 82.51, | |
| "settings": { | |
| "preset": "paper", | |
| "sample_rate": 24000, | |
| "window_seconds": 300, | |
| "overlap_seconds": 100, | |
| "lookahead_seconds": 0, | |
| "max_length": 5120, | |
| "decoding": "greedy", | |
| "attention": "sdpa", | |
| "weight_dtype": "float32", | |
| "autocast_dtype": "bfloat16", | |
| "batch_size": 1, | |
| "prompts": [ | |
| "timestamp", | |
| "downbeat_meter", | |
| "structure", | |
| "key", | |
| "chord_full", | |
| "melody_full" | |
| ], | |
| "device": "NVIDIA H800", | |
| "cuda_version": "12.6" | |
| } | |
| }, | |
| { | |
| "task": "melody", | |
| "dataset": "RWC-Pop", | |
| "metric": "full_pitch_class_F1", | |
| "score": 75.29, | |
| "settings": { | |
| "preset": "paper", | |
| "sample_rate": 24000, | |
| "window_seconds": 300, | |
| "overlap_seconds": 100, | |
| "lookahead_seconds": 0, | |
| "max_length": 5120, | |
| "decoding": "greedy", | |
| "attention": "sdpa", | |
| "weight_dtype": "float32", | |
| "autocast_dtype": "bfloat16", | |
| "batch_size": 1, | |
| "prompts": [ | |
| "timestamp", | |
| "downbeat_meter", | |
| "structure", | |
| "key", | |
| "chord_full", | |
| "melody_full" | |
| ], | |
| "device": "NVIDIA H800", | |
| "cuda_version": "12.6" | |
| } | |
| } | |
| ], | |
| "specialist_baselines": [ | |
| { | |
| "model": "ChordFormer", | |
| "task": "chord", | |
| "dataset": "osu2017", | |
| "metric": "Maj/min", | |
| "score": 86.55, | |
| "score_unrounded": 86.5497453460808, | |
| "num_tracks": 142, | |
| "aggregation": "reference_span_weighted_mean_per_track_mir_eval_majmin", | |
| "inference_protocol": "five_released_models_probability_ensemble", | |
| "vocabulary": "submission", | |
| "code_commit": "3da11c078c802b3f5a2ff0f6f8ec184a41537844", | |
| "source": "benchmarks/chordformer_results.json" | |
| }, | |
| { | |
| "model": "ChordFormer", | |
| "task": "chord", | |
| "dataset": "Chords1217", | |
| "metric": "Maj/min", | |
| "score": 83.94, | |
| "score_unrounded": 83.94339228883841, | |
| "num_tracks": 1217, | |
| "aggregation": "reference_span_weighted_mean_per_track_mir_eval_majmin", | |
| "inference_protocol": "one_released_held_out_fold_model_per_track", | |
| "vocabulary": "submission", | |
| "code_commit": "3da11c078c802b3f5a2ff0f6f8ec184a41537844", | |
| "source": "benchmarks/chordformer_results.json" | |
| }, | |
| { | |
| "model": "ChordFormer", | |
| "task": "chord", | |
| "dataset": "JAAH", | |
| "metric": "Maj/min", | |
| "score": 59.45, | |
| "score_unrounded": 59.44669210290719, | |
| "num_tracks": 113, | |
| "aggregation": "reference_span_weighted_mean_per_track_mir_eval_majmin", | |
| "inference_protocol": "five_released_models_probability_ensemble", | |
| "vocabulary": "submission", | |
| "code_commit": "3da11c078c802b3f5a2ff0f6f8ec184a41537844", | |
| "source": "benchmarks/jaah_results.json", | |
| "ci95_percent": [ | |
| 56.02619276510972, | |
| 62.7408426250374 | |
| ] | |
| } | |
| ] | |
| } | |