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Upload model from models/nemotron-speech-streaming-en-0.6b-mlx-4bit

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  1. README.md +55 -50
  2. config.json +2261 -2
  3. model.safetensors +2 -2
README.md CHANGED
@@ -1,77 +1,82 @@
1
  ---
2
- license: cc-by-4.0
3
  track_downloads: true
4
  language:
5
  - en
6
- - es
7
- - fr
8
- - de
9
- - bg
10
- - hr
11
- - cs
12
- - da
13
- - nl
14
- - et
15
- - fi
16
- - el
17
- - hu
18
- - it
19
- - lv
20
- - lt
21
- - mt
22
- - pl
23
- - pt
24
- - ro
25
- - sk
26
- - sl
27
- - sv
28
- - ru
29
- - uk
30
-
31
  pipeline_tag: automatic-speech-recognition
32
  library_name: mlx
33
  datasets:
34
  - nvidia/Granary
35
- - nemo/asr-set-3.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
36
  tags:
37
  - quantized
 
 
38
  - automatic-speech-recognition
 
39
  - speech
40
  - audio
41
- - Transducer
42
- - TDT
43
  - FastConformer
44
- - Conformer
45
- - pytorch
46
  - Parakeet
47
- base_model: nvidia/parakeet-tdt-0.6b-v3
 
 
 
 
 
48
  ---
49
 
50
- # **animaslabs/parakeet-tdt-0.6b-v3-mlx**
51
 
52
- This model was converted to MLX format from [nvidia/parakeet-tdt-0.6b-v3](https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3) using the scripts in this [github repo](https://github.com/animaslabs/mlx-models). Please refer to [original model card](https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3) for more details on the model.
53
 
54
- ## Use with mlx
55
 
56
- NOTE: parakeet-mlx and mlx-audio do not support quantized models.
57
 
58
- ### parakeet-mlx
 
 
 
 
59
 
60
- ```bash
61
- pip install -U parakeet-mlx
62
- ```
 
63
 
64
- ```bash
65
- parakeet-mlx audio.wav --model mlx-community/parakeet-tdt-0.6b-v3
66
- ```
67
-
68
- ### mlx-audio
 
 
69
 
70
- ```bash
71
- pip install -U mlx-audio
72
- ```
73
 
74
- ```bash
75
- python -m mlx_audio.stt.generate --model mlx-community/parakeet-tdt-0.6b-v3 --audio audio.wav --output somewhere
 
76
  ```
77
 
 
1
  ---
2
+ license: other
3
  track_downloads: true
4
  language:
5
  - en
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
6
  pipeline_tag: automatic-speech-recognition
7
  library_name: mlx
8
  datasets:
9
  - nvidia/Granary
10
+ - YTC
11
+ - Yodas2
12
+ - LibriLight
13
+ - librispeech_asr
14
+ - fisher_corpus
15
+ - Switchboard-1
16
+ - WSJ-0
17
+ - WSJ-1
18
+ - National-Singapore-Corpus-Part-1
19
+ - National-Singapore-Corpus-Part-6
20
+ - vctk
21
+ - voxpopuli
22
+ - europarl
23
+ - multilingual_librispeech
24
+ - fleurs
25
+ - mozilla-foundation/common_voice_8_0
26
+ - MLCommons/peoples_speech
27
+ - google/speech_commands
28
  tags:
29
  - quantized
30
+ - speech-recognition
31
+ - cache-aware ASR
32
  - automatic-speech-recognition
33
+ - streaming-asr
34
  - speech
35
  - audio
 
 
36
  - FastConformer
37
+ - RNNT
 
38
  - Parakeet
39
+ - ASR
40
+ - pytorch
41
+ - NeMo
42
+ - mlx
43
+ base_model: nvidia/nemotron-speech-streaming-en-0.6b
44
+ base_model_relation: quantized
45
  ---
46
 
47
+ # **animaslabs/nemotron-speech-streaming-en-0.6b-mlx-4bit**
48
 
49
+ This model was converted to MLX format, 4-bit quantized from [nvidia/nemotron-speech-streaming-en-0.6b](https://huggingface.co/nvidia/nemotron-speech-streaming-en-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/nemotron-speech-streaming-en-0.6b) for more details on the model.
50
 
51
+ ## Usage
52
 
53
+ Quantized models require calling `mlx.nn.quantize()` before loading weights.
54
 
55
+ ```python
56
+ import json
57
+ import mlx.nn as nn
58
+ from huggingface_hub import hf_hub_download
59
+ from parakeet_mlx.utils import from_config
60
 
61
+ # Download and load config
62
+ config_path = hf_hub_download("animaslabs/nemotron-speech-streaming-en-0.6b-mlx-4bit", "config.json")
63
+ with open(config_path) as f:
64
+ config = json.load(f)
65
 
66
+ # Build model and apply quantization structure
67
+ model = from_config(config)
68
+ nn.quantize(
69
+ model,
70
+ bits=config["quantization"]["bits"],
71
+ group_size=config["quantization"]["group_size"],
72
+ )
73
 
74
+ # Load quantized weights
75
+ weights_path = hf_hub_download("animaslabs/nemotron-speech-streaming-en-0.6b-mlx-4bit", "model.safetensors")
76
+ model.load_weights(weights_path)
77
 
78
+ # Transcribe
79
+ result = model.transcribe("audio.wav")
80
+ print(result.text)
81
  ```
82
 
config.json CHANGED
@@ -1,6 +1,2265 @@
1
  {
2
- "model_type": "parakeet-tdt",
3
- "framework": "mlx",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4
  "quantization": {
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  "bits": 4,
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  "group_size": 64
 
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  {
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+ "sample_rate": 16000,
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+ "compute_eval_loss": false,
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+ "text_field": "answer",
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+ "tarred_audio_filepaths": null
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+ "tokenizer": {
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+ "type": "bpe",
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+ "model_path": "nemo:tokenizer.model",
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+ "vocab_path": "nemo:vocab.txt",
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+ "spe_tokenizer_vocab": "nemo:tokenizer.vocab"
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+ },
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+ "preprocessor": {
56
+ "_target_": "nemo.collections.asr.modules.AudioToMelSpectrogramPreprocessor",
57
+ "sample_rate": 16000,
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+ "normalize": "NA",
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+ "window_size": 0.025,
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+ "window_stride": 0.01,
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+ "window": "hann",
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+ "features": 128,
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+ "xscaling": false,
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+ "pos_emb_max_len": 5000,
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+ "conv_kernel_size": 9,
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+ "conv_norm_type": "layer_norm",
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+ "conv_context_size": "causal",
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+ "dropout": 0.1,
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+ "dropout_pre_encoder": 0.1,
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+ "stochastic_depth_drop_prob": 0.0,
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+ "\u2581ab",
299
+ "ers",
300
+ "ess",
301
+ "ge",
302
+ "\u2581pro",
303
+ "pe",
304
+ "ate",
305
+ "\u2581su",
306
+ "\u2581com",
307
+ "\u2581but",
308
+ "\u2581all",
309
+ "est",
310
+ "qu",
311
+ "\u2581ex",
312
+ "\u2581al",
313
+ "ra",
314
+ "\u2581O",
315
+ "out",
316
+ "use",
317
+ "very",
318
+ "pp",
319
+ "\u2581Y",
320
+ "\u2581ch",
321
+ "ri",
322
+ "ist",
323
+ "\u2581v",
324
+ "\u2581lo",
325
+ "ment",
326
+ "art",
327
+ "\u2581P",
328
+ "nt",
329
+ "ab",
330
+ "\u2581one",
331
+ "\u2581N",
332
+ "ive",
333
+ "\u2581wor",
334
+ "ions",
335
+ "ort",
336
+ "\u2581L",
337
+ "\u2581by",
338
+ "ich",
339
+ "\u2581my",
340
+ "ity",
341
+ "ok",
342
+ "\u2581G",
343
+ "res",
344
+ "\u2581up",
345
+ "un",
346
+ "um",
347
+ "ea",
348
+ "ind",
349
+ "and",
350
+ "ink",
351
+ "el",
352
+ "\u2581D",
353
+ "em",
354
+ "\u2581E",
355
+ "os",
356
+ "oug",
357
+ "\u2581if",
358
+ "ca",
359
+ "\u2581out",
360
+ "\u2581int",
361
+ "ie",
362
+ "\u2581F",
363
+ "\u2581It",
364
+ "\u2581his",
365
+ "ard",
366
+ "\u2581had",
367
+ "\u2581tr",
368
+ "her",
369
+ "our",
370
+ "ies",
371
+ "ake",
372
+ "\u2581R",
373
+ "\u2581We",
374
+ "\u2581get",
375
+ "\u2581don",
376
+ "\u2581us",
377
+ "ak",
378
+ "\u2581pl",
379
+ "ect",
380
+ "ure",
381
+ "ame",
382
+ "ast",
383
+ "\u2581who",
384
+ "ack",
385
+ "\u2581le",
386
+ "\u2581sa",
387
+ "iv",
388
+ "ci",
389
+ "ide",
390
+ "\u2581tim",
391
+ "\u2581our",
392
+ "ound",
393
+ "ous",
394
+ "\u2581co",
395
+ "\u2581pe",
396
+ "ose",
397
+ "ud",
398
+ "\u2581see",
399
+ "ough",
400
+ "\u2581man",
401
+ "\u2581qu",
402
+ "\u2581You",
403
+ "so",
404
+ "ople",
405
+ "\u2581Wh",
406
+ "ong",
407
+ "ap",
408
+ "ther",
409
+ "\u2581J",
410
+ "are",
411
+ "ine",
412
+ "\u2581say",
413
+ "\u2581im",
414
+ "\u2581But",
415
+ "ings",
416
+ "\u2581has",
417
+ "\u2581ag",
418
+ "ff",
419
+ "\u2581her",
420
+ "itt",
421
+ "one",
422
+ "\u2581en",
423
+ "\u2581ar",
424
+ "\u2581fe",
425
+ "ven",
426
+ "\u2581any",
427
+ "\u2581mo",
428
+ "reat",
429
+ "ag",
430
+ "\u2581how",
431
+ "\u2581cl",
432
+ "pt",
433
+ "\u2581now",
434
+ "own",
435
+ "ber",
436
+ "\u2581him",
437
+ "\u2581act",
438
+ "hing",
439
+ "ice",
440
+ "\u2581no",
441
+ "ans",
442
+ "iz",
443
+ "\u2581fa",
444
+ "per",
445
+ "pl",
446
+ "\u2581te",
447
+ "\u2581ad",
448
+ "age",
449
+ "ree",
450
+ "\u2581tw",
451
+ "ank",
452
+ "\u2581He",
453
+ "ple",
454
+ "ite",
455
+ "ry",
456
+ "\u2581U",
457
+ "ish",
458
+ "ire",
459
+ "ue",
460
+ "\u2581In",
461
+ "\u2581she",
462
+ "ble",
463
+ "cc",
464
+ "nder",
465
+ "\u2581way",
466
+ "\u2581pr",
467
+ "ear",
468
+ "\u2581did",
469
+ "\u2581po",
470
+ "eah",
471
+ "\u2581un",
472
+ "omet",
473
+ "ence",
474
+ "ep",
475
+ "uch",
476
+ "\u2581sp",
477
+ "ach",
478
+ "og",
479
+ "ance",
480
+ "able",
481
+ "iff",
482
+ "sel",
483
+ "\u2581got",
484
+ "way",
485
+ "\u2581gr",
486
+ "alk",
487
+ "\u2581res",
488
+ "ated",
489
+ "irst",
490
+ "ick",
491
+ "ass",
492
+ "\u2581two",
493
+ "\u2581dis",
494
+ "ord",
495
+ "\u2581pre",
496
+ "ount",
497
+ "ase",
498
+ "ip",
499
+ "ult",
500
+ "ical",
501
+ "orm",
502
+ "ary",
503
+ "ace",
504
+ "\u2581spe",
505
+ "\u2581Ch",
506
+ "\u2581thr",
507
+ "\u2581imp",
508
+ "int",
509
+ "\u2581am",
510
+ "\u2581off",
511
+ "act",
512
+ "ia",
513
+ "\u2581ro",
514
+ "ress",
515
+ "\u2581per",
516
+ "\u2581fo",
517
+ "\u2581br",
518
+ "\u2581K",
519
+ "vel",
520
+ "\u2581gu",
521
+ "\u2581bo",
522
+ "ang",
523
+ "kay",
524
+ "ub",
525
+ "ign",
526
+ "\u2581may",
527
+ "ving",
528
+ "ces",
529
+ "ens",
530
+ "cl",
531
+ "\u2581lot",
532
+ "ru",
533
+ "ade",
534
+ "\u2581bet",
535
+ "\u2581bl",
536
+ "\u2581let",
537
+ "fore",
538
+ "co",
539
+ "ild",
540
+ "ning",
541
+ "xt",
542
+ "ile",
543
+ "ark",
544
+ "self",
545
+ "\u2581app",
546
+ "ory",
547
+ "du",
548
+ "\u2581day",
549
+ "\u2581St",
550
+ "ater",
551
+ "\u2581use",
552
+ "ys",
553
+ "fter",
554
+ "\u2581new",
555
+ "ious",
556
+ "ial",
557
+ "he",
558
+ "wn",
559
+ "ved",
560
+ "red",
561
+ "\u2581fl",
562
+ "iss",
563
+ "ody",
564
+ "form",
565
+ "ian",
566
+ "tain",
567
+ "\u2581bu",
568
+ "\u2581V",
569
+ "\u2581rec",
570
+ "ty",
571
+ "be",
572
+ "\u2581sc",
573
+ "ors",
574
+ "vers",
575
+ "\u2581put",
576
+ "ife",
577
+ "\u2581If",
578
+ "we",
579
+ "te",
580
+ "ject",
581
+ "ath",
582
+ "ting",
583
+ "\u2581rem",
584
+ "\u2581acc",
585
+ "ull",
586
+ "ons",
587
+ "\u2581ind",
588
+ "\u2581ser",
589
+ "\u2581ke",
590
+ "ates",
591
+ "ves",
592
+ "na",
593
+ "lic",
594
+ "\u2581des",
595
+ "\u2581its",
596
+ "ful",
597
+ "ents",
598
+ "erm",
599
+ "ac",
600
+ "ered",
601
+ "ise",
602
+ "\u2581sy",
603
+ "urn",
604
+ "\u2581em",
605
+ "oth",
606
+ "ual",
607
+ "ne",
608
+ "ward",
609
+ "ib",
610
+ "\u2581try",
611
+ "\u2581pos",
612
+ "nds",
613
+ "ft",
614
+ "get",
615
+ "ph",
616
+ "\u2581ob",
617
+ "ady",
618
+ "igh",
619
+ "ood",
620
+ "\u2581rel",
621
+ "\u2581wr",
622
+ "ug",
623
+ "ears",
624
+ "ail",
625
+ "\u2581Now",
626
+ "\u2581bit",
627
+ "ng",
628
+ "\u2581Oh",
629
+ "\u2581hel",
630
+ "ange",
631
+ "\u2581reg",
632
+ "\u2581rep",
633
+ "\u2581bel",
634
+ "\u2581sm",
635
+ "ost",
636
+ "tern",
637
+ "gr",
638
+ "\u2581own",
639
+ "\u2581end",
640
+ "pect",
641
+ "ily",
642
+ "day",
643
+ "ied",
644
+ "ific",
645
+ "ower",
646
+ "\u2581add",
647
+ "cess",
648
+ "ict",
649
+ "ible",
650
+ "\u2581bas",
651
+ "\u2581i",
652
+ "\u2581op",
653
+ "cial",
654
+ "ular",
655
+ "\u2581Be",
656
+ "ced",
657
+ "\u2581too",
658
+ "ks",
659
+ "ew",
660
+ "mer",
661
+ "\u2581ph",
662
+ "ob",
663
+ "==",
664
+ "\u2581la",
665
+ "\u2581set",
666
+ "\u2581min",
667
+ "\u2581sub",
668
+ "\u2581gen",
669
+ "atch",
670
+ "..",
671
+ "\u2581inv",
672
+ "\u2581As",
673
+ "\u2581nat",
674
+ "\u2581sl",
675
+ "\u2581num",
676
+ "av",
677
+ "ways",
678
+ "\u2581God",
679
+ "stem",
680
+ "\u2581ac",
681
+ "\u2581att",
682
+ "\u2581ev",
683
+ "\u2581def",
684
+ "llow",
685
+ "\u2581str",
686
+ "lect",
687
+ "ars",
688
+ "\u2581cr",
689
+ "\u2581Is",
690
+ "olog",
691
+ "les",
692
+ "oy",
693
+ "\u2581ask",
694
+ "\u2581inc",
695
+ "body",
696
+ "\u2581ent",
697
+ "\u2581pol",
698
+ "ness",
699
+ "ix",
700
+ "\u2581why",
701
+ "onna",
702
+ "\u2581ear",
703
+ "\u2581tak",
704
+ "\u2581Un",
705
+ "ited",
706
+ "mun",
707
+ "li",
708
+ "ute",
709
+ "ract",
710
+ "\u2581dec",
711
+ "uro",
712
+ "\u2581mak",
713
+ "\u2581fin",
714
+ "ween",
715
+ "\u2581No",
716
+ "arch",
717
+ "\u2581bec",
718
+ "gan",
719
+ "old",
720
+ "cy",
721
+ "\u2581big",
722
+ "\u2581For",
723
+ "ren",
724
+ "als",
725
+ "und",
726
+ "\u2581Al",
727
+ "\u2581All",
728
+ "ss",
729
+ "ows",
730
+ "\u2581mod",
731
+ "ock",
732
+ "\u2581id",
733
+ "ism",
734
+ "cus",
735
+ "\u2581gl",
736
+ "ably",
737
+ "\u2581ass",
738
+ "\u2581car",
739
+ "ata",
740
+ "ppen",
741
+ "led",
742
+ "\u2581sim",
743
+ "\u2581mon",
744
+ "ics",
745
+ "\u2581giv",
746
+ "cept",
747
+ "\u2581Mr",
748
+ "pan",
749
+ "\u2581pub",
750
+ "\u2581eff",
751
+ "\u2581How",
752
+ "ps",
753
+ "vern",
754
+ "end",
755
+ "hip",
756
+ "iew",
757
+ "ope",
758
+ "\u2581An",
759
+ "\u2581She",
760
+ "\u2581Com",
761
+ "ee",
762
+ "ures",
763
+ "ell",
764
+ "ouse",
765
+ "cond",
766
+ "king",
767
+ "oc",
768
+ "ues",
769
+ "ever",
770
+ "\u2581To",
771
+ "clud",
772
+ "\u2581ins",
773
+ "\u2581exp",
774
+ "\u2581old",
775
+ "\u2581mem",
776
+ "\u2581ref",
777
+ "\u2581tra",
778
+ "\u2581far",
779
+ "ave",
780
+ "rat",
781
+ "\u2581sur",
782
+ "ruct",
783
+ "rib",
784
+ "duct",
785
+ "uff",
786
+ "\u2581met",
787
+ "\u2581sch",
788
+ "ince",
789
+ "\u2581run",
790
+ "ense",
791
+ "\u2581cle",
792
+ "\u2581==",
793
+ "mon",
794
+ "ize",
795
+ "\u2581ord",
796
+ "blem",
797
+ "tin",
798
+ "\u2581Let",
799
+ "ner",
800
+ "ond",
801
+ "its",
802
+ "\u2581cor",
803
+ "land",
804
+ "\u2581cur",
805
+ "\u2581Re",
806
+ "\u2581bus",
807
+ "\u2581uh",
808
+ "air",
809
+ "ote",
810
+ "ants",
811
+ "ason",
812
+ "ric",
813
+ "\u2581el",
814
+ "\u2581cer",
815
+ "nce",
816
+ "\u2581fam",
817
+ "\u2581cap",
818
+ "uck",
819
+ "ool",
820
+ "ried",
821
+ "\u2581cou",
822
+ "\u2581fun",
823
+ "\u2581wom",
824
+ "\u2581hum",
825
+ "\u2581ty",
826
+ "\u2581ap",
827
+ "ike",
828
+ "\u2581few",
829
+ "oney",
830
+ "\u2581inf",
831
+ "ont",
832
+ "ese",
833
+ "ook",
834
+ "gy",
835
+ "uth",
836
+ "ulat",
837
+ "ieve",
838
+ "ized",
839
+ "ross",
840
+ "\u2581ple",
841
+ "\u2581um",
842
+ "\u2581val",
843
+ "\u2581equ",
844
+ "\u2581lea",
845
+ "\u2581lar",
846
+ "ah",
847
+ "eral",
848
+ "\u2581ed",
849
+ "ared",
850
+ "lish",
851
+ "arn",
852
+ "ds",
853
+ "esn",
854
+ "\u2581iss",
855
+ "\u2581ca",
856
+ "ted",
857
+ "ices",
858
+ "\u2581wee",
859
+ "ash",
860
+ "\u2581top",
861
+ "ten",
862
+ "up",
863
+ "ts",
864
+ "gin",
865
+ "con",
866
+ "ari",
867
+ "\u2581opp",
868
+ "osed",
869
+ "\u2581eas",
870
+ "\u2581ext",
871
+ "gg",
872
+ "az",
873
+ "\u2581Fr",
874
+ "ideo",
875
+ "izat",
876
+ "\u2581men",
877
+ "\u2581mom",
878
+ "\u2581ret",
879
+ "tty",
880
+ "rist",
881
+ "\u2581gra",
882
+ "alth",
883
+ "ef",
884
+ "\u2581det",
885
+ "ax",
886
+ "\u2581mat",
887
+ "chn",
888
+ "ern",
889
+ "peri",
890
+ "\u2581bre",
891
+ "\u2581Sh",
892
+ "sw",
893
+ "erat",
894
+ "\u2581sit",
895
+ "ters",
896
+ "ale",
897
+ "man",
898
+ "\u2581sol",
899
+ "ork",
900
+ "\u2581adv",
901
+ "ety",
902
+ "\u2581vis",
903
+ "\u2581med",
904
+ "uc",
905
+ "less",
906
+ "\u2581unt",
907
+ "gram",
908
+ "ets",
909
+ "ists",
910
+ "\u2581ey",
911
+ "\u2581col",
912
+ "imes",
913
+ "\u2581law",
914
+ "\u2581pri",
915
+ "sid",
916
+ "\u2581On",
917
+ "\u2581mot",
918
+ "ield",
919
+ "\u2581Do",
920
+ "\u2581At",
921
+ "ages",
922
+ "amp",
923
+ "\u2581art",
924
+ "miss",
925
+ "\u2581sk",
926
+ "alf",
927
+ "pr",
928
+ "ier",
929
+ "\u2581beh",
930
+ "\u2581Yes",
931
+ "ural",
932
+ "ime",
933
+ "\u2581wa",
934
+ "oks",
935
+ "bers",
936
+ "ger",
937
+ "ient",
938
+ "ries",
939
+ "...",
940
+ "\u2581che",
941
+ "\u2581Br",
942
+ "ird",
943
+ "\u2581Ar",
944
+ "\u2581war",
945
+ "inat",
946
+ "\u2581My",
947
+ "ital",
948
+ "wh",
949
+ "med",
950
+ "\u2581pur",
951
+ "ully",
952
+ "\u2581One",
953
+ "\u2581rat",
954
+ "ines",
955
+ "\u2581Of",
956
+ "io",
957
+ "\u2581loc",
958
+ "ret",
959
+ "ctor",
960
+ "\u2581leg",
961
+ "stit",
962
+ "ined",
963
+ "ught",
964
+ "\u2581dur",
965
+ "\u2581es",
966
+ "vent",
967
+ "aj",
968
+ "\u2581bro",
969
+ "\u2581saw",
970
+ "\u2581sec",
971
+ "ream",
972
+ "\u2581pop",
973
+ "reen",
974
+ "\u2581Ind",
975
+ "els",
976
+ "\u2581yet",
977
+ "ired",
978
+ "\u2581sw",
979
+ "tro",
980
+ "oup",
981
+ "most",
982
+ "pean",
983
+ "eds",
984
+ "ush",
985
+ "oh",
986
+ "\u2581Se",
987
+ "\u2581tea",
988
+ "ann",
989
+ "ilit",
990
+ "err",
991
+ "pend",
992
+ "ton",
993
+ "ased",
994
+ "\u2581aff",
995
+ "\u2581mor",
996
+ "\u2581dra",
997
+ "put",
998
+ "\u2581dr",
999
+ "ins",
1000
+ "uat",
1001
+ "nect",
1002
+ "cri",
1003
+ "outh",
1004
+ "\u2581ra",
1005
+ "\u2581pay",
1006
+ "ms",
1007
+ "\u2581av",
1008
+ "bs",
1009
+ "ling",
1010
+ "\u2581De",
1011
+ "\u2581Or",
1012
+ "ove",
1013
+ "\u2581Can",
1014
+ "\u2581eng",
1015
+ "ames",
1016
+ "ided",
1017
+ "\u2581Go",
1018
+ "mitt",
1019
+ "ode",
1020
+ "\u2581cre",
1021
+ "par",
1022
+ "ides",
1023
+ "pos",
1024
+ "\u2581fav",
1025
+ "\u2581air",
1026
+ "\u2581New",
1027
+ "\u2581bad",
1028
+ "\u2581six",
1029
+ "vat",
1030
+ "\u2581pat",
1031
+ "not",
1032
+ "\u2581di",
1033
+ "rop",
1034
+ "ral",
1035
+ "orn",
1036
+ "\u2581par",
1037
+ "cing",
1038
+ "\u2581aw",
1039
+ "orts",
1040
+ "ox",
1041
+ "\u2581yes",
1042
+ "cuss",
1043
+ "eng",
1044
+ "ives",
1045
+ "erms",
1046
+ "\u2581job",
1047
+ "mand",
1048
+ "ying",
1049
+ "\u2581occ",
1050
+ "aps",
1051
+ "ases",
1052
+ "\u2581Not",
1053
+ "rent",
1054
+ "ency",
1055
+ "att",
1056
+ "ised",
1057
+ "vice",
1058
+ "\u2581Eng",
1059
+ "\u2581est",
1060
+ "oked",
1061
+ "\u2581Q",
1062
+ "iron",
1063
+ "idd",
1064
+ "me",
1065
+ "unch",
1066
+ "ane",
1067
+ "\u2581z",
1068
+ "br",
1069
+ "arts",
1070
+ "\u2581fat",
1071
+ "ery",
1072
+ "anks",
1073
+ "\u2581jo",
1074
+ "\u2581mar",
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