{
 "model": "Nemotron-3-Diarization (streaming Sortformer, 8 speakers)",
 "license": "openmdw-1.1",
 "source": {
  "repo": "nvidia/Nemotron-3-Diarization",
  "revision": "f667ed73aee57d40cc39428eb768b4fd87a0a29e",
  "file": "model.safetensors",
  "sha256": "c074d86335b3b794f8fa5edc25594558f128bdb3914d27806a3a5a2e44963cb6",
  "bytes": 396954592,
  "reference": "transformers Nemotron3DiarizationForAudioFrameClassification (fp32)"
 },
 "toolchain": {
  "coreai-torch": "0.4.1",
  "coreai-core": "1.0.0b2",
  "torch": "2.9.0",
  "macos": "27.0 (26A428)"
 },
 "graph": {
  "function": "main",
  "inputs": {
   "packed": "[1, T, 512] float32: [speaker cache | FIFO | chunk rows (+ look-ahead)] left-packed at rows [0, L); rows [L, T) are ignored (zero them)",
   "valid": "[1, T] float32: 1.0 for rows < L, 0.0 after"
  },
  "outputs": {
   "logits": "[1, T*8, 8] float32 speaker logits at 10 ms; rows [0, L*8) are real"
  },
  "T": {
   "streaming": 541,
   "offline": 684
  },
  "host_side": "sigmoid, the 8x average pool to encoder rate, the speaker cache (AOSC + FIFO), segmentation"
 },
 "host": {
  "frame_s": 0.01,
  "encoder_frame_s": 0.08,
  "subsampling": 8,
  "num_speakers": 8,
  "hidden": 512,
  "profiles": {
   "streaming": {
    "T": 541,
    "fifo_length": 264,
    "update_period": 222,
    "modes": {
     "low_latency": {
      "chunk": 9,
      "lookahead": 4
     },
     "very_low_latency": {
      "chunk": 6,
      "lookahead": 2
     },
     "ultra_low_latency": {
      "chunk": 3,
      "lookahead": 1
     }
    },
    "chunking": "per chunk mel from its own audio slice: chunk 0 = audio[:((c+la)*8-1)*160+200] center=True; chunk k>=1 starts at 160*k*c*8-256 and holds (c+la)*8*160+400 samples, center=False; the first chunk that would run past the audio takes the rest, is the last (no look-ahead) and emits its true mel frame count"
   },
   "offline": {
    "T": 684,
    "fifo_length": 40,
    "update_period": 300,
    "chunk": 340,
    "lookahead": 40,
    "chunking": "whole-recording mel (center=True) -> embeds -> chunks of 340 rows + up to 40 look-ahead rows; output cut to the mel frame count"
   }
  },
  "step": "rows = [cache | FIFO | chunk]; logits = graph(rows)[:L*8]; probs = avg_pool8(sigmoid(logits)); emit logits[(n_cache+n_fifo)*8 : +min(n_chunk*8, n_emit)]; then the cache update",
  "speaker_cache": {
   "length": 264,
   "silence_frames_per_speaker": 1,
   "prediction_score_threshold": 0.25,
   "latest_frames_score_boost": 0.05,
   "min_positive_scores": 16,
   "strong_boost": {
    "frames": 24,
    "add": 1.3862943611198906
   },
   "weak_boost": {
    "frames": 48,
    "add": 0.6931471805599453
   },
   "update": "transformers Nemotron3DiarizationSpeakerCache.update/_compress @ 4b28d51, line by line (host_loop.py)",
   "score_dtype": "float64 from the float32 probabilities (transformers: float32; see host_loop.py)",
   "topk_ties": "lower index first",
   "sentinel": "the silence row (row N: silence_embeds, zero probs)"
  },
  "segments": "transformers extract_speaker_dict: per speaker, runs of sigmoid(logits) > 0.5; overlaps kept"
 },
 "mel": {
  "sample_rate": 16000,
  "preemphasis": 0.9700000286102295,
  "preemphasis_first_sample": "kept",
  "n_fft": 512,
  "win_length": 400,
  "hop": 160,
  "window": "hann_window_400.f32le, centered in 512 (zeros at [0,56) and [456,512))",
  "power": "|rFFT|^2 (as sqrt(re^2+im^2)^2 in float32)",
  "n_mels": 128,
  "fmin": 0.0,
  "fmax": 8000.0,
  "norm": "slaney",
  "log": "log(mel + 2^-24)",
  "log_guard": 5.960464477539063e-08,
  "normalize": null,
  "center_pad": "256 zeros each side when center=True (first chunk / offline), none otherwise",
  "valid_frames": "center: n // 160; not center: (n - 512) // 160 + 1",
  "stacking": "8 frames -> 1024 (zero-pad the frame count to a multiple of 8 in the log-mel domain)"
 },
 "assets": {
  "embedder_projection.f32le": {
   "shape": [
    512,
    1024
   ],
   "what": "model.audio_tower.embedder.projection.weight (Linear 1024->512, no bias); embeds = stacked @ W.T",
   "sha256": "add02ccfa230d319e82b55a49e6e2b0ae3d01fb326621b10e04e5aa5dd03d651",
   "dtype": "float32 little-endian, C order"
  },
  "silence_embeds.f32le": {
   "shape": [
    512
   ],
   "what": "silence_embeds: the speaker cache's silence row (1 per speaker)",
   "sha256": "d4417b3c0eabdf7c47032fac2b5b5a7ee83d819a6ddda8fd8eaf74e2b5cc4ac7",
   "dtype": "float32 little-endian, C order"
  },
  "mel_filters_128x257.f32le": {
   "shape": [
    128,
    257
   ],
   "what": "librosa.filters.mel(sr=16000, n_fft=512, n_mels=128, fmin=0, fmax=8000, norm='slaney'); bit-identical to the transformers feature extractor's",
   "sha256": "bce5ec5f194a5913f6508cee5a85512e7bad2352db8fc28f5c6ff75af8b09137",
   "dtype": "float32 little-endian, C order"
  },
  "hann_window_400.f32le": {
   "shape": [
    400
   ],
   "what": "torch.hann_window(400, periodic=False); bit-identical to the feature extractor's",
   "sha256": "c427e2029118cf789649e5a4d439b6115d0dd0cbf95dcd22f65e3c848add8c5b",
   "dtype": "float32 little-endian, C order"
  }
 },
 "bundles": {
  "n3d_streaming_float16.aimodel": {
   "profile": "streaming",
   "T": 541,
   "dtype": "float16",
   "target": "macOS 27, Apple silicon GPU (compiled at load)",
   "compute_preference": "gpu",
   "bytes": 197982173,
   "mb": 198.0,
   "tree_sha256": "52563c95a40394c0b587e1550495b12bbb424dfcbfb5983a857f38db237d38f0",
   "contract": {
    "function": "main",
    "inputs": {
     "packed": {
      "shape": [
       1,
       541,
       512
      ],
      "dtype": "float32"
     },
     "valid": {
      "shape": [
       1,
       541
      ],
      "dtype": "float32"
     }
    },
    "outputs": {
     "logits": {
      "shape": [
       1,
       4328,
       8
      ],
      "dtype": "float32"
     }
    },
    "states": []
   }
  },
  "n3d_streaming_float16.h18p.aimodelc": {
   "profile": "streaming",
   "T": 541,
   "dtype": "float16",
   "target": "iOS 27, iPhone 17 Pro GPU (compiled ahead of time, h18p)",
   "compute_preference": "gpu",
   "bytes": 198238645,
   "mb": 198.2,
   "tree_sha256": "1e2840464bc246ab7508e1d5e4bf1b6a29e2f55159ff8fabf65c609303ccdb2d",
   "compiled_from": "n3d_streaming_float16.aimodel",
   "contract": "that of n3d_streaming_float16.aimodel",
   "aot": {
    "command": "xcrun coreai-build compile n3d_streaming_float16.aimodel --output <dir> --platform iOS --architecture h18p --preferred-compute gpu --min-deployment-version 27.0",
    "coreai_build": "3600.83.1",
    "ane_regions": 0
   }
  },
  "n3d_offline_float16.aimodel": {
   "profile": "offline",
   "T": 684,
   "dtype": "float16",
   "target": "macOS 27, Apple silicon GPU (compiled at load)",
   "compute_preference": "gpu",
   "bytes": 198018769,
   "mb": 198.0,
   "tree_sha256": "93c99942a3b311824c90c6ccbdc0042eb259331a12a60ae414040963d001210d",
   "contract": {
    "function": "main",
    "inputs": {
     "packed": {
      "shape": [
       1,
       684,
       512
      ],
      "dtype": "float32"
     },
     "valid": {
      "shape": [
       1,
       684
      ],
      "dtype": "float32"
     }
    },
    "outputs": {
     "logits": {
      "shape": [
       1,
       5472,
       8
      ],
      "dtype": "float32"
     }
    },
    "states": []
   }
  },
  "n3d_offline_float16.h18p.aimodelc": {
   "profile": "offline",
   "T": 684,
   "dtype": "float16",
   "target": "iOS 27, iPhone 17 Pro GPU (compiled ahead of time, h18p)",
   "compute_preference": "gpu",
   "bytes": 198275246,
   "mb": 198.3,
   "tree_sha256": "8494215fba0bddc0d3a6b99673664ce6826d6e47882bdfde744abd7506be10ff",
   "compiled_from": "n3d_offline_float16.aimodel",
   "contract": "that of n3d_offline_float16.aimodel",
   "aot": {
    "command": "xcrun coreai-build compile n3d_offline_float16.aimodel --output <dir> --platform iOS --architecture h18p --preferred-compute gpu --min-deployment-version 27.0",
    "coreai_build": "3600.83.1",
    "ane_regions": 0
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  }
 },
 "notes": [
  "compute_preference: load with SpecializationOptions(preferredComputeUnitKind: .gpu); the .h18p.aimodelc bundles were also compiled with --preferred-compute gpu.",
  "The float32 bundles are for parity only (CPU) and are not shipped: export_n3d.py --dtype float32 [--profile offline] rebuilds them."
 ]
}