add

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+seg_dict filter=lfs diff=lfs merge=lfs -text

am.mvn

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+</Nnet>

config.yaml

@@ -0,0 +1,116 @@
+# This is an example that demonstrates how to configure a model file.
+# You can modify the configuration according to your own requirements.
+
+# to print the register_table:
+# from funasr.register import tables
+# tables.print()
+
+# network architecture
+model: Conformer
+model_conf:
+    ctc_weight: 0.3
+    lsm_weight: 0.1     # label smoothing option
+    length_normalized_loss: false
+
+# encoder
+encoder: ConformerEncoder
+encoder_conf:
+    output_size: 512
+    attention_heads: 16
+    linear_units: 1536
+    num_blocks: 32
+    dropout_rate: 0.1
+    positional_dropout_rate: 0.1
+    attention_dropout_rate: 0.0
+    input_layer: linear
+    normalize_before: true
+    pos_enc_layer_type: rel_pos
+    selfattention_layer_type: rel_selfattn
+    activation_type: swish
+    macaron_style: true
+    use_cnn_module: true
+    cnn_module_kernel: 5
+
+# decoder
+decoder: TransformerDecoder
+decoder_conf:
+    attention_heads: 16
+    linear_units: 1536
+    num_blocks: 16
+    dropout_rate: 0.1
+    positional_dropout_rate: 0.1
+    self_attention_dropout_rate: 0.0
+    src_attention_dropout_rate: 0.0
+
+
+# frontend related
+frontend: WavFrontend
+frontend_conf:
+    fs: 16000
+    window: hamming
+    n_mels: 80
+    frame_length: 25
+    frame_shift: 10
+    lfr_m: 7
+    lfr_n: 6
+
+specaug: SpecAug
+specaug_conf:
+    apply_time_warp: true
+    time_warp_window: 5
+    time_warp_mode: bicubic
+    apply_freq_mask: true
+    freq_mask_width_range:
+    - 0
+    - 30
+    num_freq_mask: 2
+    apply_time_mask: true
+    time_mask_width_range:
+    - 0
+    - 40
+    num_time_mask: 2
+
+train_conf:
+  accum_grad: 1
+  grad_clip: 5
+  max_epoch: 150
+  val_scheduler_criterion:
+      - valid
+      - acc
+  best_model_criterion:
+  -   - valid
+      - acc
+      - max
+  keep_nbest_models: 10
+  log_interval: 50
+
+optim: adam
+optim_conf:
+   lr: 0.0005
+scheduler: warmuplr
+scheduler_conf:
+   warmup_steps: 30000
+
+dataset: AudioDataset
+dataset_conf:
+    index_ds: IndexDSJsonl
+    batch_sampler: DynamicBatchLocalShuffleSampler
+    batch_type: example # example or length
+    batch_size: 1 # if batch_type is example, batch_size is the numbers of samples; if length, batch_size is source_token_len+target_token_len;
+    max_token_length: 2048 # filter samples if source_token_len+target_token_len > max_token_length,
+    buffer_size: 500
+    shuffle: True
+    num_workers: 0
+
+tokenizer: CharTokenizer
+tokenizer_conf:
+  unk_symbol: <unk>
+  split_with_space: true
+
+
+ctc_conf:
+    dropout_rate: 0.0
+    ctc_type: builtin
+    reduce: true
+    ignore_nan_grad: true
+normalize: null

configuration.json

@@ -0,0 +1,14 @@
+{
+  "framework": "pytorch",
+  "task" : "auto-speech-recognition",
+  "model": {"type" : "funasr"},
+  "pipeline": {"type":"funasr-pipeline"},
+  "model_name_in_hub": {
+    "ms":"", 
+    "hf":""},
+  "file_path_metas": {
+    "init_param":"model.pt", 
+    "config":"config.yaml",
+    "tokenizer_conf": {"token_list": "tokens.json", "seg_dict_file": "seg_dict"},
+    "frontend_conf":{"cmvn_file": "am.mvn"}}
+}

model.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:888d52b31d06323e70237ff97d37e962b88a4bf1c5de8e0b82163f0d41b226d2
+size 936637532

seg_dict

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e2049cead30e04361064c7555891e8ce0ee32a0dbe61b06f340a1d49071a97b8
+size 74060738

tokens.json

@@ -0,0 +1,4202 @@
+[
+    "<blank>",
+    "<s>",
+    "</s>",
+    "<OOV>",
+    "<gbg>",
+    "the",
+    "and",
+    "to",
+    "of",
+    "a",
+    "i",
+    "that",
+    "you",
+    "in",
+    "is",
+    "it",
+    "we",
+    "for",
+    "so",
+    "this",
+    "have",
+    "on",
+    "are",
+    "was",
+    "with",
+    "not",
+    "be",
+    "as",
+    "but",
+    "at",
+    "they",
+    "he",
+    "can",
+    "do",
+    "what",
+    "or",
+    "one",
+    "know",
+    "an",
+    "like",
+    "all",
+    "if",
+    "re@@",
+    "from",
+    "my",
+    "there",
+    "me",
+    "about",
+    "will",
+    "our",
+    "your",
+    "just",
+    "by",
+    "had",
+    "his",
+    "how",
+    "would",
+    "think",
+    "which",
+    "when",
+    "very",
+    "then",
+    "d@@",
+    "s",
+    "more",
+    "some",
+    "in@@",
+    "ed",
+    "were",
+    "it's",
+    "out",
+    "s@@",
+    "up",
+    "going",
+    "get",
+    "t@@",
+    "a@@",
+    "people",
+    "their",
+    "now",
+    "p@@",
+    "e",
+    "because",
+    "them",
+    "time",
+    "she",
+    "her",
+    "has",
+    "ing",
+    "no",
+    "t",
+    "k@@",
+    "who",
+    "us",
+    "g@@",
+    "really",
+    "b@@",
+    "been",
+    "go",
+    "these",
+    "see",
+    "also",
+    "here",
+    "o@@",
+    "right",
+    "well",
+    "en@@",
+    "es",
+    "want",
+    "am",
+    "e@@",
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+]