Upload model from models/parakeet-rnnt-0.6b-mlx-4bit

README.md

@@ -0,0 +1,73 @@
+---
+license: cc-by-4.0
+track_downloads: true
+language:
+- en
+pipeline_tag: automatic-speech-recognition
+library_name: mlx
+datasets:
+- librispeech_asr
+- fisher_corpus
+- Switchboard-1
+- WSJ-0
+- WSJ-1
+- National-Singapore-Corpus-Part-1
+- National-Singapore-Corpus-Part-6
+- vctk
+- voxpopuli
+- europarl
+- multilingual_librispeech
+- mozilla-foundation/common_voice_8_0
+- MLCommons/peoples_speech
+tags:
+- quantized
+- automatic-speech-recognition
+- speech
+- audio
+- Transducer
+- FastConformer
+- Conformer
+- pytorch
+- NeMo
+- hf-asr-leaderboard
+- mlx
+base_model: nvidia/parakeet-rnnt-0.6b
+base_model_relation: quantized
+---
+
+# **animaslabs/parakeet-rnnt-0.6b-mlx-4bit**
+
+This model was converted to MLX format, 4-bit quantized from [nvidia/parakeet-rnnt-0.6b](https://huggingface.co/nvidia/parakeet-rnnt-0.6b) using the scripts in this [github repo](https://github.com/animaslabs/mlx-models). Please refer to [original model card](https://huggingface.co/nvidia/parakeet-rnnt-0.6b) for more details on the model.
+
+## Usage
+
+Quantized models require calling `mlx.nn.quantize()` before loading weights.
+
+```python
+import json
+import mlx.nn as nn
+from huggingface_hub import hf_hub_download
+from parakeet_mlx.utils import from_config
+
+# Download and load config
+config_path = hf_hub_download("animaslabs/parakeet-rnnt-0.6b-mlx-4bit", "config.json")
+with open(config_path) as f:
+    config = json.load(f)
+
+# Build model and apply quantization structure
+model = from_config(config)
+nn.quantize(
+    model,
+    bits=config["quantization"]["bits"],
+    group_size=config["quantization"]["group_size"],
+)
+
+# Load quantized weights
+weights_path = hf_hub_download("animaslabs/parakeet-rnnt-0.6b-mlx-4bit", "model.safetensors")
+model.load_weights(weights_path)
+
+# Transcribe
+result = model.transcribe("audio.wav")
+print(result.text)
+```
+

config.json

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+{
+  "sample_rate": 16000,
+  "compute_eval_loss": false,
+  "log_prediction": true,
+  "rnnt_reduction": "mean_volume",
+  "skip_nan_grad": false,
+  "model_defaults": {
+    "enc_hidden": 1024,
+    "pred_hidden": 640,
+    "joint_hidden": 640
+  },
+  "train_ds": {
+    "manifest_filepath": "/disk1/NVIDIA/datasets/LibriSpeech_NeMo/librivox-train-all.json",
+    "sample_rate": 16000,
+    "batch_size": 16,
+    "shuffle": true,
+    "num_workers": 8,
+    "pin_memory": true,
+    "use_start_end_token": false,
+    "trim_silence": false,
+    "max_duration": 16.7,
+    "min_duration": 0.1,
+    "is_tarred": false,
+    "tarred_audio_filepaths": null,
+    "shuffle_n": 2048,
+    "bucketing_strategy": "fully_randomized",
+    "bucketing_batch_size": null
+  },
+  "validation_ds": {
+    "manifest_filepath": "/disk1/NVIDIA/datasets/LibriSpeech_NeMo/librivox-dev-clean.json",
+    "sample_rate": 16000,
+    "batch_size": 16,
+    "shuffle": false,
+    "use_start_end_token": false,
+    "num_workers": 8,
+    "pin_memory": true
+  },
+  "test_ds": {
+    "manifest_filepath": null,
+    "sample_rate": 16000,
+    "batch_size": 16,
+    "shuffle": false,
+    "use_start_end_token": false,
+    "num_workers": 8,
+    "pin_memory": true
+  },
+  "tokenizer": {
+    "dir": "/disk3/datasets/suno_asr_set3_tokenizer/tokenizer_spe_bpe_v1024/",
+    "type": "bpe",
+    "model_path": "nemo:tokenizer.model",
+    "vocab_path": "nemo:vocab.txt",
+    "spe_tokenizer_vocab": "nemo:tokenizer.vocab"
+  },
+  "preprocessor": {
+    "_target_": "nemo.collections.asr.modules.AudioToMelSpectrogramPreprocessor",
+    "sample_rate": 16000,
+    "normalize": "per_feature",
+    "window_size": 0.025,
+    "window_stride": 0.01,
+    "window": "hann",
+    "features": 80,
+    "n_fft": 512,
+    "log": true,
+    "frame_splicing": 1,
+    "dither": 1e-05,
+    "pad_to": 0,
+    "pad_value": 0.0
+  },
+  "spec_augment": {
+    "_target_": "nemo.collections.asr.modules.SpectrogramAugmentation",
+    "freq_masks": 2,
+    "time_masks": 10,
+    "freq_width": 27,
+    "time_width": 0.05
+  },
+  "encoder": {
+    "_target_": "nemo.collections.asr.modules.ConformerEncoder",
+    "feat_in": 80,
+    "feat_out": -1,
+    "n_layers": 24,
+    "d_model": 1024,
+    "subsampling": "dw_striding",
+    "subsampling_factor": 8,
+    "subsampling_conv_channels": 256,
+    "causal_downsampling": false,
+    "reduction": null,
+    "reduction_position": null,
+    "reduction_factor": 1,
+    "ff_expansion_factor": 4,
+    "self_attention_model": "rel_pos",
+    "n_heads": 8,
+    "att_context_size": [
+      -1,
+      -1
+    ],
+    "att_context_style": "regular",
+    "xscaling": true,
+    "untie_biases": true,
+    "pos_emb_max_len": 5000,
+    "conv_kernel_size": 9,
+    "conv_norm_type": "batch_norm",
+    "conv_context_size": null,
+    "dropout": 0.1,
+    "dropout_pre_encoder": 0.1,
+    "dropout_emb": 0.0,
+    "dropout_att": 0.1
+  },
+  "decoder": {
+    "_target_": "nemo.collections.asr.modules.RNNTDecoder",
+    "normalization_mode": null,
+    "random_state_sampling": false,
+    "blank_as_pad": true,
+    "prednet": {
+      "pred_hidden": 640,
+      "pred_rnn_layers": 2,
+      "t_max": null,
+      "dropout": 0.2
+    },
+    "vocab_size": 1024
+  },
+  "joint": {
+    "_target_": "nemo.collections.asr.modules.RNNTJoint",
+    "log_softmax": null,
+    "preserve_memory": false,
+    "fuse_loss_wer": true,
+    "fused_batch_size": 16,
+    "jointnet": {
+      "joint_hidden": 640,
+      "activation": "relu",
+      "dropout": 0.2,
+      "encoder_hidden": 1024,
+      "pred_hidden": 640
+    },
+    "num_classes": 1024,
+    "vocabulary": [
+      "<unk>",
+      "\u2581t",
+      "\u2581th",
+      "\u2581a",
+      "\u2581i",
+      "\u2581the",
+      "re",
+      "\u2581w",
+      "\u2581s",
+      "\u2581o",
+      "in",
+      "at",
+      "er",
+      "ou",
+      "nd",
+      "\u2581c",
+      "\u2581b",
+      "\u2581h",
+      "on",
+      "\u2581m",
+      "\u2581f",
+      "ing",
+      "\u2581to",
+      "en",
+      "\u2581p",
+      "\u2581and",
+      "\u2581d",
+      "es",
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+      "an",
+      "ll",
+      "\u2581y",
+      "\u2581l",
+      "ed",
+      "\u2581of",
+      "\u2581in",
+      "it",
+      "is",
+      "\u2581you",
+      "\u2581that",
+      "ar",
+      "\u2581g",
+      "\u2581n",
+      "as",
+      "om",
+      "\u2581it",
+      "ic",
+      "ve",
+      "\u2581e",
+      "\u2581wh",
+      "\u2581be",
+      "us",
+      "le",
+      "al",
+      "ion",
+      "ow",
+      "\u2581we",
+      "\u2581re",
+      "\u2581is",
+      "ut",
+      "ot",
+      "ent",
+      "\u2581on",
+      "et",
+      "\u2581ha",
+      "ay",
+      "ct",
+      "\u2581he",
+      "id",
+      "\u2581for",
+      "\u2581st",
+      "ver",
+      "ly",
+      "ro",
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+      "\u2581so",
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+      "\u2581this",
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+      "\u2581u",
+      "se",
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+      "ce",
+      "ch",
+      "im",
+      "ith",
+      "\u2581as",
+      "\u2581k",
+      "\u2581an",
+      "\u2581was",
+      "\u2581j",
+      "\u2581with",
+      "ir",
+      "\u2581go",
+      "ra",
+      "\u2581do",
+      "\u2581have",
+      "\u2581li",
+      "\u2581sh",
+      "\u2581se",
+      "\u2581they",
+      "\u2581are",
+      "am",
+      "ht",
+      "\u2581but",
+      "ation",
+      "\u2581not",
+      "th",
+      "\u2581r",
+      "ally",
+      "ad",
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+      "\u2581or",
+      "\u2581com",
+      "ould",
+      "\u2581can",
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+      "\u2581ne",
+      "ight",
+      "\u2581ch",
+      "\u2581de",
+      "\u2581con",
+      "\u2581at",
+      "\u2581mo",
+      "ant",
+      "oo",
+      "il",
+      "\u2581me",
+      "\u2581what",
+      "\u2581there",
+      "ter",
+      "pe",
+      "\u2581ab",
+      "\u2581su",
+      "ere",
+      "ck",
+      "\u2581pro",
+      "\u2581al",
+      "\u2581fr",
+      "\u2581kn",
+      "\u2581all",
+      "ers",
+      "\u2581like",
+      "ge",
+      "\u2581ex",
+      "\u2581som",
+      "ul",
+      "\u2581your",
+      "\u2581v",
+      "pp",
+      "use",
+      "\u2581if",
+      "ess",
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+      "\u2581know",
+      "out",
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+      "\u2581just",
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+      "\u2581one",
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+      "\u2581my",
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+      "\u2581from",
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+      "\u2581about",
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+      "\u2581out",
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+      "\u2581some",
+      "\u2581int",
+      "\u2581by",
+      "\u2581pl",
+      "\u2581get",
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+      "\u2581when",
+      "\u2581don",
+      "her",
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+      "\u2581think",
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+      "\u2581then",
+      "\u2581our",
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+      "\u2581tim",
+      "\u2581how",
+      "ven",
+      "\u2581tr",
+      "\u2581who",
+      "\u2581them",
+      "ure",
+      "\u2581ar",
+      "\u2581ye",
+      "\u2581more",
+      "\u2581going",
+      "ect",
+      "\u2581sa",
+      "\u2581cl",
+      "\u2581had",
+      "\u2581now",
+      "\u2581which",
+      "\u2581here",
+      "ous",
+      "\u2581their",
+      "\u2581tw",
+      "so",
+      "\u2581has",
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+      "\u2581co",
+      "\u2581ta",
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+      "\u2581were",
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+      "\u2581peop",
+      "ough",
+      "\u2581no",
+      "\u2581really",
+      "\u2581any",
+      "\u2581people",
+      "\u2581want",
+      "\u2581she",
+      "\u2581en",
+      "\u2581fa",
+      "\u2581te",
+      "ame",
+      "ine",
+      "\u2581qu",
+      "red",
+      "\u2581im",
+      "\u2581right",
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+      "\u2581act",
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+      "king",
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+      "\u2581see",
+      "\u2581time",
+      "\u2581these",
+      "ci",
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+      "\u2581say",
+      "\u2581also",
+      "\u2581fe",
+      "per",
+      "\u2581ag",
+      "\u2581man",
+      "ore",
+      "\u2581un",
+      "pt",
+      "\u2581her",
+      "\u2581look",
+      "ong",
+      "ice",
+      "\u2581very",
+      "ff",
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+      "\u2581comp",
+      "\u2581did",
+      "itt",
+      "\u2581well",
+      "\u2581other",
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+      "ree",
+      "hing",
+      "\u2581lo",
+      "reat",
+      "\u2581cont",
+      "\u2581part",
+      "\u2581into",
+      "nder",
+      "\u2581been",
+      "are",
+      "\u2581am",
+      "ans",
+      "\u2581sp",
+      "\u2581two",
+      "ue",
+      "\u2581way",
+      "age",
+      "\u2581where",
+      "ite",
+      "\u2581dis",
+      "\u2581than",
+      "\u2581every",
+      "\u2581pr",
+      "\u2581po",
+      "ag",
+      "\u2581need",
+      "ach",
+      "iff",
+      "ence",
+      "pl",
+      "own",
+      "\u2581ac",
+      "ble",
+      "\u2581over",
+      "iz",
+      "\u2581work",
+      "\u2581res",
+      "\u2581make",
+      "\u2581could",
+      "\u2581off",
+      "ually",
+      "\u2581ro",
+      "\u2581back",
+      "able",
+      "ip",
+      "ry",
+      "\u2581him",
+      "\u2581cour",
+      "ber",
+      "\u2581pre",
+      "\u2581fir",
+      "\u2581spe",
+      "ap",
+      "ars",
+      "\u2581diff",
+      "ire",
+      "\u2581somet",
+      "\u2581imp",
+      "\u2581those",
+      "\u2581comm",
+      "ance",
+      "ick",
+      "\u2581even",
+      "ated",
+      "way",
+      "sel",
+      "\u2581let",
+      "\u2581br",
+      "ty",
+      "\u2581per",
+      "int",
+      "\u2581first",
+      "\u2581thr",
+      "\u2581under",
+      "ah",
+      "\u2581may",
+      "\u2581cou",
+      "\u2581new",
+      "ress",
+      "act",
+      "\u2581gr",
+      "ep",
+      "\u2581said",
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+      "\u2581good",
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+      "\u2581does",
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+      "\u2581af",
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+      "\u2581app",
+      "\u2581lot",
+      "\u2581things",
+      "\u2581tra",
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+      "\u2581bl",
+      "\u2581little",
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+      "\u2581differe",
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+      "\u2581got",
+      "ens",
+      "\u2581gu",
+      "\u2581kind",
+      "\u2581much",
+      "ord",
+      "\u2581through",
+      "ition",
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+      "\u2581down",
+      "\u2581actually",
+      "\u2581something",
+      "ang",
+      "ru",
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+      "\u2581fl",
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+      "\u2581ra",
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+      "ict",
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+      "\u2581sc",
+      "vel",
+      "\u2581bet",
+      "\u2581tal",
+      "\u2581yeah",
+      "\u2581use",
+      "fore",
+      "\u2581bu",
+      "\u2581start",
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+      "\u2581day",
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+      "\u2581should",
+      "\u2581fo",
+      "\u2581ho",
+      "\u2581hel",
+      "\u2581ind",
+      "\u2581uh",
+      "na",
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+      "other",
+      "\u2581ke",
+      "\u2581call",
+      "\u2581most",
+      "\u2581ok",
+      "\u2581different",
+      "\u2581em",
+      "ting",
+      "ple",
+      "\u2581being",
+      "\u2581bo",
+      "ning",
+      "\u2581too",
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+      "ark",
+      "og",
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+      "\u2581ser",
+      "ether",
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+      "\u2581mean",
+      "\u2581many",
+      "\u2581court",
+      "\u2581bel",
+      "ade",
+      "\u2581la",
+      "ved",
+      "\u2581des",
+      "\u2581rec",
+      "\u2581jo",
+      "\u2581dec",
+      "ves",
+      "\u2581before",
+      "\u2581put",
+      "self",
+      "\u2581point",
+      "te",
+      "\u2581ev",
+      "form",
+      "ents",
+      "\u2581add",
+      "ody",
+      "thing",
+      "\u2581case",
+      "\u2581pers",
+      "\u2581cons",
+      "iss",
+      "\u2581three",
+      "oth",
+      "\u2581ph",
+      "\u2581come",
+      "\u2581find",
+      "\u2581why",
+      "ull",
+      "\u2581show",
+      "\u2581bas",
+      "\u2581great",
+      "ily",
+      "\u2581rel",
+      "\u2581sm",
+      "\u2581its",
+      "\u2581fact",
+      "\u2581pos",
+      "ool",
+      "ments",
+      "ise",
+      "nds",
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+      "\u2581try",
+      "ual",
+      "ful",
+      "erm",
+      "\u2581inter",
+      "ons",
+      "\u2581quest",
+      "\u2581sub",
+      "we",
+      "vers",
+      "\u2581supp",
+      "\u2581feel",
+      "\u2581same",
+      "ub",
+      "ates",
+      "urn",
+      "ert",
+      "\u2581inv",
+      "day",
+      "\u2581rep",
+      "igh",
+      "\u2581sy",
+      "\u2581inst",
+      "\u2581long",
+      "\u2581still",
+      "\u2581okay",
+      "ft",
+      "ific",
+      "atch",
+      "ought",
+      "ath",
+      "\u2581own",
+      "\u2581made",
+      "ix",
+      "ced",
+      "ks",
+      "lic",
+      "\u2581wr",
+      "de",
+      "\u2581cr",
+      "\u2581att",
+      "\u2581ob",
+      "\u2581world",
+      "\u2581sure",
+      "ward",
+      "\u2581bit",
+      "\u2581life",
+      "\u2581person",
+      "\u2581pres",
+      "ph",
+      "\u2581vide",
+      "\u2581reg",
+      "\u2581end",
+      "ject",
+      "ange",
+      "\u2581fin",
+      "ied",
+      "pect",
+      "\u2581didn",
+      "\u2581around",
+      "ian",
+      "\u2581car",
+      "ible",
+      "\u2581sim",
+      "ever",
+      "\u2581sch",
+      "ating",
+      "\u2581pol",
+      "\u2581set",
+      "\u2581oh",
+      "cy",
+      "\u2581real",
+      "\u2581import",
+      "\u2581count",
+      "\u2581um",
+      "\u2581next",
+      "cial",
+      "les",
+      "\u2581hu",
+      "\u2581acc",
+      "\u2581might",
+      "\u2581ent",
+      "\u2581doing",
+      "\u2581ins",
+      "\u2581gen",
+      "\u2581play",
+      "\u2581cle",
+      "\u2581another",
+      "ady",
+      "ular",
+      "ib",
+      "ways",
+      "ered",
+      "ility",
+      "ities",
+      "\u2581op",
+      "\u2581def",
+      "\u2581years",
+      "\u2581never",
+      "ower",
+      "ram",
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+      "\u2581sl",
+      "onna",
+      "ail",
+      "ren",
+      "ute",
+      "\u2581gonna",
+      "\u2581big",
+      "\u2581give",
+      "der",
+      "ount",
+      "\u2581ap",
+      "kes",
+      "\u2581state",
+      "\u2581cor",
+      "\u2581min",
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+}

model.safetensors

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+size 631129538

model_config.yaml

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+sample_rate: 16000
+compute_eval_loss: false
+log_prediction: true
+rnnt_reduction: mean_volume
+skip_nan_grad: false
+model_defaults:
+  enc_hidden: 1024
+  pred_hidden: 640
+  joint_hidden: 640
+train_ds:
+  manifest_filepath: /disk1/NVIDIA/datasets/LibriSpeech_NeMo/librivox-train-all.json
+  sample_rate: 16000
+  batch_size: 16
+  shuffle: true
+  num_workers: 8
+  pin_memory: true
+  use_start_end_token: false
+  trim_silence: false
+  max_duration: 16.7
+  min_duration: 0.1
+  is_tarred: false
+  tarred_audio_filepaths: null
+  shuffle_n: 2048
+  bucketing_strategy: fully_randomized
+  bucketing_batch_size: null
+validation_ds:
+  manifest_filepath: /disk1/NVIDIA/datasets/LibriSpeech_NeMo/librivox-dev-clean.json
+  sample_rate: 16000
+  batch_size: 16
+  shuffle: false
+  use_start_end_token: false
+  num_workers: 8
+  pin_memory: true
+test_ds:
+  manifest_filepath: null
+  sample_rate: 16000
+  batch_size: 16
+  shuffle: false
+  use_start_end_token: false
+  num_workers: 8
+  pin_memory: true
+tokenizer:
+  dir: /disk3/datasets/suno_asr_set3_tokenizer/tokenizer_spe_bpe_v1024/
+  type: bpe
+  model_path: nemo:f644e5ef786442deb7c1726c7db0d44f_tokenizer.model
+  vocab_path: nemo:94b39775a827410cb52d0b8d95177f1e_vocab.txt
+  spe_tokenizer_vocab: nemo:1cc2984fcca649148e4a5afcd991ddb0_tokenizer.vocab
+preprocessor:
+  _target_: nemo.collections.asr.modules.AudioToMelSpectrogramPreprocessor
+  sample_rate: 16000
+  normalize: per_feature
+  window_size: 0.025
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+  features: 80
+  n_fft: 512
+  log: true
+  frame_splicing: 1
+  dither: 1.0e-05
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+  time_width: 0.05
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+  causal_downsampling: false
+  reduction: null
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+  reduction_factor: 1
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+  random_state_sampling: false
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+  prednet:
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+- j
+- x
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+target: nemo.collections.asr.models.rnnt_bpe_models.EncDecRNNTBPEModel
+nemo_version: 1.19.0rc0

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vocab.txt

@@ -0,0 +1,1023 @@
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