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ibm-granite
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granite-speech-4.1-2b-nar

Feature Extraction
Transformers
Safetensors
granite_speech_nar
speech
asr
non-autoregressive
ctc
speech_recognition
automatic_speech_recognition
custom_code
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Avihu commited on
Commit
99a4df9
·
1 Parent(s): f272034

update encoder bpe vocab

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Files changed (8) hide show
  1. config.json +65 -55
  2. configuration_granite_speech_nar.py +5 -1
  3. merges.txt +0 -0
  4. model.safetensors +2 -2
  5. modeling_granite_speech_nar.py +5 -4
  6. processing_granite_speech_nar.py +0 -1
  7. tokenizer.json +26 -1
  8. tokenizer_config.json +4 -773
config.json CHANGED
@@ -1,84 +1,94 @@
1
  {
 
 
 
2
  "auto_map": {
3
  "AutoConfig": "configuration_granite_speech_nar.GraniteSpeechNarConfig",
4
  "AutoFeatureExtractor": "feature_extraction_granite_speech_nar.GraniteSpeechNarFeatureExtractor",
5
- "AutoProcessor": "processing_granite_speech_nar.GraniteSpeechNarProcessor",
6
- "AutoModel": "modeling_granite_speech_nar.GraniteSpeechNarForASR"
7
  },
8
- "architectures": [
9
- "GraniteSpeechNarForASR"
10
- ],
11
- "model_type": "granite_speech_nar",
12
- "torch_dtype": "bfloat16",
13
  "encoder_config": {
14
- "model_type": "granite_speech_nar_encoder",
15
- "input_dim": 160,
16
- "num_layers": 16,
17
- "hidden_dim": 1024,
 
 
 
 
18
  "feedforward_mult": 4,
 
 
 
 
 
19
  "num_heads": 8,
20
- "dim_head": 128,
21
  "output_dim": 348,
22
- "context_size": 200,
23
- "max_pos_emb": 512,
24
- "dropout": 0.1,
25
  "pred_dropout": 0.25,
26
- "conv_kernel_size": 15,
27
- "conv_expansion_factor": 2,
28
- "self_conditioning_layer": 8,
29
- "bpe_output_dim": 100353,
30
- "bpe_pooling_window": 4,
31
- "initializer_range": 0.02
32
  },
 
 
 
 
 
 
 
 
 
33
  "projector_config": {
34
- "model_type": "granite_speech_nar_projector",
 
 
 
35
  "encoder_dim": 1024,
 
 
36
  "llm_dim": 2048,
37
- "downsample_rate": 5,
 
 
38
  "num_encoder_layers": 4,
39
- "hidden_size": 2048,
40
  "num_heads": 32,
41
- "num_layers": 2,
42
- "dropout_prob": 0.1,
43
- "block_size": 15,
44
- "mlp_ratio": 2,
45
- "layernorm_eps": 1e-06,
46
- "attn_bias": true,
47
- "mlp_bias": true
48
  },
 
49
  "text_config": {
50
- "model_type": "granite",
51
- "vocab_size": 100352,
 
 
 
 
 
 
 
52
  "hidden_size": 2048,
 
53
  "intermediate_size": 4096,
54
- "num_hidden_layers": 40,
 
 
 
55
  "num_attention_heads": 16,
 
56
  "num_key_value_heads": 4,
57
- "hidden_act": "silu",
58
- "max_position_embeddings": 4096,
59
- "initializer_range": 0.1,
60
- "rms_norm_eps": 1e-05,
61
- "use_cache": true,
62
  "pad_token_id": 100256,
63
- "bos_token_id": 100257,
64
- "eos_token_id": 100257,
65
- "tie_word_embeddings": true,
66
  "rope_parameters": {
67
  "rope_theta": 10000,
68
  "rope_type": "default"
69
  },
70
- "attention_bias": false,
71
- "attention_dropout": 0.0,
72
- "mlp_bias": false,
73
- "embedding_multiplier": 12,
74
- "logits_scaling": 8,
75
- "residual_multiplier": 0.22,
76
- "attention_multiplier": 0.0078125
77
  },
78
- "encoder_layer_indices": [4, 8, 12, -1],
79
- "scale_projected_embeddings": true,
80
- "blank_token_id": 100257,
81
- "min_edit_sequence_length": 8,
82
- "ce_loss_lambda": 0.0,
83
- "encoder_ctc_loss_lambda": 0.0
84
  }
 
1
  {
2
+ "architectures": [
3
+ "GraniteSpeechNarForASR"
4
+ ],
5
  "auto_map": {
6
  "AutoConfig": "configuration_granite_speech_nar.GraniteSpeechNarConfig",
7
  "AutoFeatureExtractor": "feature_extraction_granite_speech_nar.GraniteSpeechNarFeatureExtractor",
8
+ "AutoModel": "modeling_granite_speech_nar.GraniteSpeechNarForASR",
9
+ "AutoProcessor": "processing_granite_speech_nar.GraniteSpeechNarProcessor"
10
  },
11
+ "blank_token_id": 100257,
12
+ "ce_loss_lambda": 0.02,
13
+ "dtype": "bfloat16",
 
 
14
  "encoder_config": {
15
+ "blank_token_id": 100257,
16
+ "bpe_output_dim": 100352,
17
+ "bpe_pooling_window": 4,
18
+ "context_size": 200,
19
+ "conv_expansion_factor": 2,
20
+ "conv_kernel_size": 15,
21
+ "dim_head": 128,
22
+ "dropout": 0.1,
23
  "feedforward_mult": 4,
24
+ "hidden_dim": 1024,
25
+ "initializer_range": 0.02,
26
+ "input_dim": 160,
27
+ "max_pos_emb": 512,
28
+ "model_type": "granite_speech_nar_encoder",
29
  "num_heads": 8,
30
+ "num_layers": 16,
31
  "output_dim": 348,
 
 
 
32
  "pred_dropout": 0.25,
33
+ "self_conditioning_layer": 8
 
 
 
 
 
34
  },
35
+ "encoder_ctc_loss_lambda": 0.8,
36
+ "encoder_layer_indices": [
37
+ 4,
38
+ 8,
39
+ 12,
40
+ -1
41
+ ],
42
+ "min_edit_sequence_length": 8,
43
+ "model_type": "granite_speech_nar",
44
  "projector_config": {
45
+ "attn_bias": true,
46
+ "block_size": 15,
47
+ "downsample_rate": 5,
48
+ "dropout_prob": 0.1,
49
  "encoder_dim": 1024,
50
+ "hidden_size": 2048,
51
+ "layernorm_eps": 1e-06,
52
  "llm_dim": 2048,
53
+ "mlp_bias": true,
54
+ "mlp_ratio": 2,
55
+ "model_type": "granite_speech_nar_projector",
56
  "num_encoder_layers": 4,
 
57
  "num_heads": 32,
58
+ "num_layers": 2
 
 
 
 
 
 
59
  },
60
+ "scale_projected_embeddings": true,
61
  "text_config": {
62
+ "_name_or_path": "ibm-granite/granite-4.0-1b-base",
63
+ "attention_bias": false,
64
+ "attention_dropout": 0.0,
65
+ "attention_multiplier": 0.0078125,
66
+ "bos_token_id": 100257,
67
+ "dtype": "bfloat16",
68
+ "embedding_multiplier": 12,
69
+ "eos_token_id": 100257,
70
+ "hidden_act": "silu",
71
  "hidden_size": 2048,
72
+ "initializer_range": 0.1,
73
  "intermediate_size": 4096,
74
+ "logits_scaling": 8,
75
+ "max_position_embeddings": 4096,
76
+ "mlp_bias": false,
77
+ "model_type": "granite",
78
  "num_attention_heads": 16,
79
+ "num_hidden_layers": 40,
80
  "num_key_value_heads": 4,
 
 
 
 
 
81
  "pad_token_id": 100256,
82
+ "residual_multiplier": 0.22,
83
+ "rms_norm_eps": 1e-05,
 
84
  "rope_parameters": {
85
  "rope_theta": 10000,
86
  "rope_type": "default"
87
  },
88
+ "tie_word_embeddings": true,
89
+ "use_cache": true,
90
+ "vocab_size": 100352
 
 
 
 
91
  },
92
+ "tie_word_embeddings": true,
93
+ "transformers_version": "5.8.0.dev0"
 
 
 
 
94
  }
configuration_granite_speech_nar.py CHANGED
@@ -40,7 +40,7 @@ class GraniteSpeechNarEncoderConfig(PreTrainedConfig):
40
  Layer index at which self-conditioning (mid-layer CTC feedback) is applied.
41
  Defaults to `num_layers // 2`.
42
  bpe_output_dim (`int`, *optional*):
43
- Vocabulary size for the BPE CTC head (shifted by +1 for blank). If None, BPE head is disabled.
44
  bpe_pooling_window (`int`, *optional*, defaults to 4):
45
  Window size for posterior-weighted pooling before the BPE CTC head.
46
 
@@ -78,6 +78,7 @@ class GraniteSpeechNarEncoderConfig(PreTrainedConfig):
78
  self_conditioning_layer: int | None = None
79
  bpe_output_dim: int | None = None
80
  bpe_pooling_window: int = 4
 
81
  initializer_range: float = 0.02
82
 
83
  def __post_init__(self, **kwargs):
@@ -208,6 +209,9 @@ class GraniteSpeechNarConfig(PreTrainedConfig):
208
  if self.blank_token_id is None:
209
  self.blank_token_id = self.text_config.eos_token_id
210
 
 
 
 
211
  super().__post_init__(**kwargs)
212
 
213
 
 
40
  Layer index at which self-conditioning (mid-layer CTC feedback) is applied.
41
  Defaults to `num_layers // 2`.
42
  bpe_output_dim (`int`, *optional*):
43
+ Vocabulary size for the BPE CTC head (same as LLM vocab, blank reuses eos_token_id). If None, BPE head is disabled.
44
  bpe_pooling_window (`int`, *optional*, defaults to 4):
45
  Window size for posterior-weighted pooling before the BPE CTC head.
46
 
 
78
  self_conditioning_layer: int | None = None
79
  bpe_output_dim: int | None = None
80
  bpe_pooling_window: int = 4
81
+ blank_token_id: int | None = None
82
  initializer_range: float = 0.02
83
 
84
  def __post_init__(self, **kwargs):
 
209
  if self.blank_token_id is None:
210
  self.blank_token_id = self.text_config.eos_token_id
211
 
212
+ # Propagate blank_token_id to encoder config
213
+ self.encoder_config.blank_token_id = self.blank_token_id
214
+
215
  super().__post_init__(**kwargs)
216
 
217
 
merges.txt DELETED
The diff for this file is too large to render. See raw diff
 
model.safetensors CHANGED
@@ -1,3 +1,3 @@
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  version https://git-lfs.github.com/spec/v1
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- size 4509384522
 
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+ oid sha256:a187681b05e9598028b6177bba4588a27a76b97ab6840870877d69e1770a5094
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+ size 4509382472
modeling_granite_speech_nar.py CHANGED
@@ -834,10 +834,10 @@ class GraniteSpeechNarCTCEncoder(GraniteSpeechNarPreTrainedModel):
834
  loss = (
835
  F.ctc_loss(
836
  log_probs.transpose(0, 1),
837
- labels + 1,
838
  lengths,
839
  label_lengths,
840
- blank=0,
841
  reduction="sum",
842
  zero_infinity=True,
843
  )
@@ -944,10 +944,11 @@ class GraniteSpeechNarForASR(GraniteSpeechNarPreTrainedModel):
944
  bpe_logits_flat: torch.Tensor,
945
  bpe_lengths: list[int],
946
  ) -> list[torch.Tensor]:
947
- """GPU CTC greedy decode: argmax -> unique_consecutive -> remove blank -> shift."""
 
948
  preds_flat = bpe_logits_flat.argmax(dim=-1)
949
  per_sample = preds_flat.split(bpe_lengths)
950
- return [(collapsed := torch.unique_consecutive(seq))[collapsed != 0] - 1 for seq in per_sample]
951
 
952
  def _add_insertion_slots(self, token_ids: torch.Tensor) -> torch.Tensor:
953
  """Insert blank tokens between each CTC token as editing slots for the LLM."""
 
834
  loss = (
835
  F.ctc_loss(
836
  log_probs.transpose(0, 1),
837
+ labels,
838
  lengths,
839
  label_lengths,
840
+ blank=self.config.blank_token_id,
841
  reduction="sum",
842
  zero_infinity=True,
843
  )
 
944
  bpe_logits_flat: torch.Tensor,
945
  bpe_lengths: list[int],
946
  ) -> list[torch.Tensor]:
947
+ """GPU CTC greedy decode: argmax -> unique_consecutive -> remove blank."""
948
+ blank_id = self.config.blank_token_id
949
  preds_flat = bpe_logits_flat.argmax(dim=-1)
950
  per_sample = preds_flat.split(bpe_lengths)
951
+ return [(collapsed := torch.unique_consecutive(seq))[collapsed != blank_id] for seq in per_sample]
952
 
953
  def _add_insertion_slots(self, token_ids: torch.Tensor) -> torch.Tensor:
954
  """Insert blank tokens between each CTC token as editing slots for the LLM."""
processing_granite_speech_nar.py CHANGED
@@ -26,7 +26,6 @@ if is_torch_available():
26
  class GraniteSpeechNarProcessor(ProcessorMixin):
27
  """Processor combining audio feature extraction and tokenizer for GraniteSpeechNar."""
28
 
29
- feature_extractor_class = "AutoFeatureExtractor"
30
  tokenizer_class = "AutoTokenizer"
31
 
32
  def __init__(self, feature_extractor: GraniteSpeechNarFeatureExtractor, tokenizer=None, **kwargs):
 
26
  class GraniteSpeechNarProcessor(ProcessorMixin):
27
  """Processor combining audio feature extraction and tokenizer for GraniteSpeechNar."""
28
 
 
29
  tokenizer_class = "AutoTokenizer"
30
 
31
  def __init__(self, feature_extractor: GraniteSpeechNarFeatureExtractor, tokenizer=None, **kwargs):
tokenizer.json CHANGED
@@ -888,7 +888,32 @@
888
  }
889
  ]
890
  },
891
- "post_processor": null,
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
892
  "decoder": {
893
  "type": "ByteLevel",
894
  "add_prefix_space": true,
 
888
  }
889
  ]
890
  },
891
+ "post_processor": {
892
+ "type": "TemplateProcessing",
893
+ "single": [
894
+ {
895
+ "Sequence": {
896
+ "id": "A",
897
+ "type_id": 0
898
+ }
899
+ }
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+ ],
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+ "pair": [
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+ {
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+ "Sequence": {
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+ "type_id": 0
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+ }
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+ },
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+ "Sequence": {
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+ "id": "B",
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+ "type_id": 1
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+ }
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+ }
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+ ],
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+ "special_tokens": {}
916
+ },
917
  "decoder": {
918
  "type": "ByteLevel",
919
  "add_prefix_space": true,
tokenizer_config.json CHANGED
@@ -1,783 +1,14 @@
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- "add_bos_token": false,
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2
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3
+ "backend": "tokenizers",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4
  "bos_token": "<|end_of_text|>",
5
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  "padding_side": "left",
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14
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