pere commited on
Commit
4319ef6
1 Parent(s): 4c7a829

Update model

Browse files
.gitattributes CHANGED
@@ -34,3 +34,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
  *.onnx_data filter=lfs diff=lfs merge=lfs -text
 
 
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
  *.onnx_data filter=lfs diff=lfs merge=lfs -text
37
+ *.onnx* filter=lfs diff=lfs merge=lfs -text
README.md CHANGED
@@ -1,93 +1,269 @@
1
  ---
 
2
  language:
3
  - 'no'
4
- license: apache-2.0
5
- base_model: NbAiLab/nb-whisper-tiny-v0.7
 
 
 
 
 
 
6
  tags:
7
  - audio
8
  - asr
9
  - automatic-speech-recognition
10
  - hf-asr-leaderboard
11
- model-index:
12
- - name: nb-whisper-tiny-v0.7-semantic
13
- results: []
 
 
 
 
 
 
 
14
  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
15
 
16
- <!-- This model card has been generated automatically according to the information Keras had access to. You should
17
- probably proofread and complete it, then remove this comment. -->
18
-
19
- # nb-whisper-tiny-v0.7-semantic
20
-
21
- This model is a fine-tuned version of [NbAiLab/nb-whisper-tiny-v0.7](https://huggingface.co/NbAiLab/nb-whisper-tiny-v0.7) on the NbAiLab/ncc_speech_styling_v4 dataset.
22
- It achieves the following results on the evaluation set:
23
- - step: 249
24
- - validation_nst_loss: 0.6579
25
- - train_loss: 1.2508
26
- - validation_nst_wer: 8.8029
27
- - validation_nst_cer: 2.9662
28
- - validation_nst_exact_wer: 9.6358
29
- - validation_nst_exact_cer: 3.0880
30
- - validation_clean_stortinget_no_loss: 0.7202
31
- - validation_clean_stortinget_no_wer: 16.5324
32
- - validation_clean_stortinget_no_cer: 9.1926
33
- - validation_clean_stortinget_no_exact_wer: 20.6476
34
- - validation_clean_stortinget_no_exact_cer: 9.9178
35
-
36
- ## Model description
37
-
38
- More information needed
39
-
40
- ## Intended uses & limitations
41
-
42
- More information needed
43
-
44
- ## Training and evaluation data
45
-
46
- More information needed
47
-
48
- ## Training procedure
49
-
50
- ### Training hyperparameters
51
-
52
- The following hyperparameters were used during training:
53
- - learning_rate: 2.5e-05
54
- - lr_scheduler_type: linear
55
- - per_device_train_batch_size: 32
56
- - total_train_batch_size_per_node: 128
57
- - total_train_batch_size: 1024
58
- - total_optimization_steps: 250
59
- - starting_optimization_step: None
60
- - finishing_optimization_step: 250
61
- - num_train_dataset_workers: 32
62
- - num_hosts: 8
63
- - total_num_training_examples: 256,000
64
- - steps_per_epoch: _To be computed after first epoch_
65
- - num_beams: None
66
- - weight_decay: 0.01
67
- - adam_beta1: 0.9
68
- - adam_beta2: 0.98
69
- - adam_epsilon: 0.00015
70
- - dropout: True
71
- - bpe_dropout_probability: 0.2
72
- - activation_dropout_probability: 0.1
73
-
74
- ### Training results
75
-
76
- | step | validation_nst_loss | train_loss | validation_nst_wer | validation_nst_cer | validation_nst_exact_wer | validation_nst_exact_cer | validation_clean_stortinget_no_loss | validation_clean_stortinget_no_wer | validation_clean_stortinget_no_cer | validation_clean_stortinget_no_exact_wer | validation_clean_stortinget_no_exact_cer |
77
- |:----:|:-------------------:|:----------:|:------------------:|:------------------:|:------------------------:|:------------------------:|:-----------------------------------:|:----------------------------------:|:----------------------------------:|:----------------------------------------:|:----------------------------------------:|
78
- | 0 | 0.5155 | 1.4782 | 7.9155 | 2.5430 | 8.7103 | 2.6640 | 0.7153 | 15.8148 | 8.6090 | 19.7201 | 9.3061 |
79
- | 40 | 0.5328 | 1.3581 | 8.6232 | 2.8926 | 9.6031 | 3.0477 | 0.7058 | 17.0843 | 9.6747 | 21.3213 | 10.4075 |
80
- | 80 | 0.6321 | 1.1988 | 8.8464 | 3.1266 | 9.7447 | 3.2629 | 0.7131 | 16.8712 | 9.3548 | 20.9062 | 10.0570 |
81
- | 120 | 0.6456 | 1.1956 | 8.7757 | 3.0306 | 9.6630 | 3.1585 | 0.7165 | 16.7243 | 9.2521 | 20.8113 | 9.9704 |
82
- | 160 | 0.6455 | 1.2386 | 8.7648 | 2.9784 | 9.6195 | 3.1081 | 0.7188 | 16.7030 | 9.2259 | 20.8967 | 9.9658 |
83
- | 200 | 0.6576 | 1.1753 | 8.6777 | 2.9336 | 9.4888 | 3.0559 | 0.7202 | 16.5917 | 9.1859 | 20.7188 | 9.9205 |
84
- | 240 | 0.6577 | 1.1923 | 8.9226 | 2.9923 | 9.7338 | 3.1100 | 0.7214 | 16.6272 | 9.2176 | 20.7211 | 9.9396 |
85
- | 249 | 0.6579 | 1.2508 | 8.8029 | 2.9662 | 9.6358 | 3.0880 |
86
- | 249 | 0.7202 | 1.2508 | 16.5324 | 9.1926 | 20.6476 | 9.9178 |
87
-
88
-
89
- ### Framework versions
90
-
91
- - Transformers 4.34.1
92
- - Datasets 2.15.0
93
- - Tokenizers 0.14.1
 
1
  ---
2
+ license: apache-2.0
3
  language:
4
  - 'no'
5
+ - nb
6
+ - nn
7
+ - en
8
+ datasets:
9
+ - NbAiLab/ncc_speech
10
+ - NbAiLab/NST
11
+ - NbAiLab/NPSC
12
+ base_model: openai/whisper-tiny
13
  tags:
14
  - audio
15
  - asr
16
  - automatic-speech-recognition
17
  - hf-asr-leaderboard
18
+ metrics:
19
+ - wer
20
+ - cer
21
+ library_name: transformers
22
+ pipeline_tag: automatic-speech-recognition
23
+ widget:
24
+ - src: https://datasets-server.huggingface.co/assets/google/fleurs/--/nb_no/train/1/audio/audio.mp3
25
+ example_title: FLEURS sample 1
26
+ - src: https://datasets-server.huggingface.co/assets/google/fleurs/--/nb_no/train/4/audio/audio.mp3
27
+ example_title: FLEURS sample 2
28
  ---
29
+ # Finetuned Semantic model.
30
+
31
+ This model is trained 200 additional steps on top of the main model. The output from this model is less verbatim than when using the main model. The style might be more suited for instance for subtitling of videos since the goal is to use as few words as possible to express the essence of what is said.
32
+
33
+ # NB-Whisper Tiny (Release Candidate)
34
+
35
+ **IMPORTANT:** These models are currently Release Candidates. We are in the final stages of testing. If everything proceeds smoothly, we plan to officially release the models later this month.
36
+
37
+ Introducing the **_Norwegian NB-Whisper Tiny model_**, proudly developed by the National Library of Norway. NB-Whisper is a cutting-edge series of models designed for automatic speech recognition (ASR) and speech translation. These models are based on the work of [OpenAI's Whisper](https://arxiv.org/abs/2212.04356). Each model in the series has been trained for 250,000 steps, utilizing a diverse dataset of 8 million samples. These samples consist of aligned audio clips, each 30 seconds long, culminating in a staggering 66,000 hours of speech. For an in-depth understanding of our training methodology and dataset composition, keep an eye out for our upcoming article.
38
+
39
+ | Model Size | Parameters | Model |
40
+ |------------|------------|------------|
41
+ | Tiny | 39M | [NB-Whisper Tiny](https://huggingface.co/NbAiLabBeta/nb-whisper-tiny) |
42
+ | Base | 74M | [NB-Whisper Base](https://huggingface.co/NbAiLabBeta/nb-whisper-base) |
43
+ | Small | 244M | [NB-Whisper Small](https://huggingface.co/NbAiLabBeta/nb-whisper-small) |
44
+ | Medium | 769M | [NB-Whisper Medium](https://huggingface.co/NbAiLabBeta/nb-whisper-medium) |
45
+ | Large | 1550M | [NB-Whisper Large](https://huggingface.co/NbAiLabBeta/nb-whisper-large) |
46
+
47
+
48
+
49
+ ### Specialised Models
50
+ While the main models are suitable for most transcription task, we demonstrate how easy it is to change the output of the main model. The following models are trained 250 additional steps from the main models above, and might be suitable for more targetted use cases:
51
+ - **Verbatim version**: This lower-cased variant is more literal and suitable for tasks requiring detailed transcription, such as linguistic analysis.
52
+ - **Semantic version**: This variant focuses less on verbatim accuracy but captures the essence of content, ideal for meeting minutes and subtitling.
53
+
54
+
55
+ | Model Size | Parameters | Verbatim version | Semantic version |
56
+ |------------|------------|------------|------------------|
57
+ | Tiny | 39M | [Tiny - verbatim](https://huggingface.co/NbAiLabBeta/nb-whisper-tiny-verbatim) | [Tiny - semantic](https://huggingface.co/NbAiLabBeta/nb-whisper-tiny-semantic) |
58
+ | Base | 74M | [Base - verbatim](https://huggingface.co/NbAiLabBeta/nb-whisper-base-verbatim) | [Base - semantic](https://huggingface.co/NbAiLabBeta/nb-whisper-base-semantic) |
59
+ | Small | 244M | [Small - verbatim](https://huggingface.co/NbAiLabBeta/nb-whisper-small-verbatim) | [Small - semantic](https://huggingface.co/NbAiLabBeta/nb-whisper-small-semantic) |
60
+ | Medium | 769M | [Medium - verbatim](https://huggingface.co/NbAiLabBeta/nb-whisper-medium-verbatim) | [Medium - semantic](https://huggingface.co/NbAiLabBeta/nb-whisper-medium-semantic) |
61
+ | Large | 1550M | [Large - verbatim](https://huggingface.co/NbAiLabBeta/nb-whisper-large-verbatim) | [Large - semantic](https://huggingface.co/NbAiLabBeta/nb-whisper-large-semantic) |
62
+
63
+
64
+ ### Model Description
65
+
66
+ - **Developed by:** [NB AI-Lab](https://ai.nb.no/)
67
+ - **Shared by:** [NB AI-Lab](https://ai.nb.no/)
68
+ - **Model type:** `whisper`
69
+ - **Language(s) (NLP):** Norwegian, Norwegian Bokmål, Norwegian Nynorsk, English
70
+ - **License:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0)
71
+ - **Trained from model:** [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny)
72
+ - **Code Repository:** https://github.com/NbAiLab/nb-whisper/
73
+ - **Paper:** _Coming soon_
74
+ - **Demo:** _See Spaces on this page_
75
+
76
+
77
+ ## How to Use the Models
78
+
79
+ ### Online Demos
80
+ You can try the models directly through the HuggingFace Inference API, accessible on the right side of this page. Be aware that initially, the model needs to load and will run on limited CPU capacity, which might be slow. To enhance your experience, we are temporarily hosting some models on TPUs for a few days, significantly boosting their performance. Explore these under the **Spaces** section on the [Main Page](https://huggingface.co/NbAiLabBeta/).
81
+
82
+ ### Local Setup with HuggingFace
83
+ Alternatively, you can run the models locally. The Tiny, Base, and Small models are optimized for CPU execution. For the Medium and Large models, we recommend a system equipped with a GPU to ensure efficient processing. Setting up and using these models with HuggingFace's Transformers is straightforward, provided you have [Python](https://www.python.org/downloads/) installed on your machine. For practical demonstrations, refer to examples using this [sample mp3 file](https://github.com/NbAiLab/nb-whisper/raw/main/audio/king.mp3).
84
+
85
+ ```bash
86
+ # Download the sample file
87
+ $ wget -N https://github.com/NbAiLab/nb-whisper/raw/main/audio/king.mp3
88
+
89
+ # Install necessary libraries.
90
+ $ pip install transformers>=4.35.2
91
+ ```
92
+
93
+ After this is done, you should be able to run this in Python:
94
+
95
+ ```python
96
+ from transformers import pipeline
97
+
98
+ # Load the model
99
+ asr = pipeline("automatic-speech-recognition", "NbAiLabBeta/nb-whisper-tiny-semantic")
100
+
101
+ #transcribe
102
+ asr("king.mp3", generate_kwargs={'task': 'transcribe', 'language': 'no'})
103
+
104
+ ```
105
+
106
+ <details>
107
+ <summary>Expected output</summary>
108
+
109
+ ```json
110
+ {
111
+ {'text': ' Nordmenn er nordlendinger, trøndere, sørlendinger og folk fra alle andre regioner. Nordmenn er også innvandret fra Afghanistan, Pakistan, Polen, Sverige, Somalia og Syria. Det er ikke alltid så lett å si hvor vi er fra, hvilken nasjonalitet vi er fra. Hvilken nasjonalitet vi er fra. Hvilken nasjonalitet vi er fra. Hvilken nasjonalitet vi er fra. Hvilken nasjonalitet vi er fra. Hvilken nasjonalitet vi er fra. Hvilken nasjonalitet vi er fra.'}
112
+ }
113
+ ```
114
+ </details>
115
+
116
+ #### Extended HuggingFace
117
+ Examining the output above, we see that there are multiple repetitions at the end. This is because the default length is 30 seconds and the video is 1:25 minutes. By passing the ```chunk_lengt_s``` argument, we can transcribe longer file. The examples below also illustrates how to transcribe to English or Nynorsk, and how to get timestamps for sentences and words.
118
+
119
+ ```python
120
+ # Long Transcripts
121
+ asr("king.mp3", chunk_length_s=30, generate_kwargs={'task': 'transcribe', 'language': 'no'})
122
+
123
+ # Return Timestamps
124
+ asr("king.mp3", chunk_length_s=30, return_timestamps=True, generate_kwargs={'task': 'transcribe', 'language': 'no'})
125
+
126
+ # Return Word Level Timestamps
127
+ asr("king.mp3", chunk_length_s=30, return_timestamps="word", generate_kwargs={'task': 'transcribe', 'language': 'no'})
128
+
129
+ # Transcribe to Nynorsk
130
+ asr("king.mp3", chunk_length_s=30, generate_kwargs={'task': 'transcribe', 'language': 'nn'})
131
+
132
+ # Transcribe to English
133
+ asr("king.mp3", chunk_length_s=30, generate_kwargs={'task': 'transcribe', 'language': 'en'})
134
+
135
+ ```
136
+ <details>
137
+ <summary>Expected output</summary>
138
+
139
+ Long transcripts:
140
+ ```json
141
+ {
142
+ {'text': ' Nordmenn er nordlendinger, trøndere, sørlendinger og folk fra alle andre regioner. Nordmenn er også innvandret fra Afghanistan, Pakistan, Polen, Sverige, Somalia og Syria. Det er ikke alltid så lett å si hvor vi er fra, hvilken nasjonalitet vi er fra. Hvilken nasjonalitet vi er fra. Hvilken nasjonalitet vi er fra. Hvilken nasjonalitet vi er fra. Hvilken nasjonalitet vi er fra. Hvilken nasjonalitet vi er fra, hvilken nasjonalitet vi tilhører. Det vi kaller hjem, er der hjertet vårt er, og det kan ikke alltid plasseres innenfor landegrenser. Nordmenn er jenter som er glad i jenter, gutter som er glad i gutter, og jenter og gutter som er glad i hverandre. Nordmenn trommer på Gud, Allah, Altet og ingenting. Nordmenn liker Grieg, Kygo, Helbilis og Kari Bremnes. Med andre ord, Norge er dere. Norge er oss. Mitt største håp for Norge er at vi skal klare å ta vare på hverandre, at vi skal bygge dette landet videre på tillit, fellesskap og raushet.'}
143
+ }
144
+ ```
145
+
146
+ Timestamps:
147
+ ```json
148
+ {
149
+ {'text': ' Nordmenn er nordlendinger, trøndere, sørlendinger og folk fra alle andre regioner. Nordmenn er også innvandret fra Afghanistan, Pakistan, Polen, Sverige, Somalia og Syria. Det er ikke alltid så lett å si hvor vi er fra, hvilken nasjonalitet vi er fra. Hvilken nasjonalitet vi er fra. hvilken nasjonalitet vi tilhører. Det vi kaller hjem, er der hjertet vårt er, og det kan ikke alltid plasseres innenfor landegrenser. Nordmenn er jenter som er glad i jenter, gutter som er glad i gutter, og jenter og gutter som er glad i hverandre. Nordmenn trommer på Gud, Allah, Altet og ingenting. Nordmenn liker Grieg, Kygo, Helbiles og Kari Bremnes. Med andre ord, Norge er dere. Norge er oss. Mitt største håp for Norge er at vi skal klare å ta vare på hverandre, at vi skal bygge dette landet videre på tillit, fellesskap og raushet.',
150
+ 'chunks': [{'timestamp': (0.0, 5.46),
151
+ 'text': ' Nordmenn er nordlendinger, trøndere, sørlendinger'},
152
+ {'timestamp': (5.52, 8.68), 'text': ' og folk fra alle andre regioner.'},
153
+ {'timestamp': (8.68, 16.64),
154
+ 'text': ' Nordmenn er også innvandret fra Afghanistan, Pakistan, Polen, Sverige, Somalia og Syria.'},
155
+ {'timestamp': (16.64, 13.3),
156
+ 'text': ' Det er ikke alltid så lett å si hvor vi er fra, hvilken nasjonalitet vi er fra.'},
157
+ {'timestamp': (13.32, 30.28),
158
+ 'text': ' Hvilken nasjonalitet vi er fra. hvilken nasjonalitet vi tilhører.'},
159
+ {'timestamp': (32.52, 39.16),
160
+ 'text': ' Det vi kaller hjem, er der hjertet vårt er, og det kan ikke alltid plasseres'},
161
+ {'timestamp': (39.16, 42.0), 'text': ' innenfor landegrenser.'},
162
+ {'timestamp': (42.0, 46.74),
163
+ 'text': ' Nordmenn er jenter som er glad i jenter, gutter som er glad i gutter,'},
164
+ {'timestamp': (46.74, 51.12),
165
+ 'text': ' og jenter og gutter som er glad i hverandre.'},
166
+ {'timestamp': (51.16, 57.42),
167
+ 'text': ' Nordmenn trommer på Gud, Allah, Altet og ingenting.'},
168
+ {'timestamp': (57.42, 64.3),
169
+ 'text': ' Nordmenn liker Grieg, Kygo, Helbiles og Kari Bremnes.'},
170
+ {'timestamp': (64.34, 71.24),
171
+ 'text': ' Med andre ord, Norge er dere. Norge er oss.'},
172
+ {'timestamp': (71.24, 78.04),
173
+ 'text': ' Mitt største håp for Norge er at vi skal klare å ta vare på hverandre,'},
174
+ {'timestamp': (78.12, 84.68),
175
+ 'text': ' at vi skal bygge dette landet videre på tillit, fellesskap og raushet.'}]}
176
+ }
177
+ ```
178
+
179
+ Word Level Timestamps:
180
+ ```json
181
+ {
182
+ {"text": "Nordmenn er nordlendinger, trøndere, sørlendinger og folk fra alle andre regioner. Nordmenn er også innvandret fra Afghanistan, Pakistan, Polen, Sverige, Somalia og Syria. Det er ikke alltid så lett å si hvor vi er fra, hvilken nasjonalitet vi tilhører. Det vi kaller hjem, er der hjertet vårt er, og det kan ikke alltid plasseres innenfor landegrenser. Nordmenn er jenter som er glad i jenter, gutter som er glad i gutter, og jenter og gutter som er glad i hverandre. Nordmenn trommer på Gud, Allah, Altet og ingenting. Nordmenn liker Grieg, Kygo, Helbilis og Kari Bremnes. Med andre ord, Norge er dere. Norge er oss. Mitt største håp for Norge er at vi skal klare å ta vare på hverandre, at vi skal bygge dette landet videre på tillit, fellesskap og raushet.",
183
+ "chunks": [
184
+ {"text": "Nordmenn", "timestamp": [0.72, 1.42]},
185
+ {"text": "er", "timestamp": [1.42, 1.74]},
186
+ // ... more chunks ...
187
+ {"text": "raushet.", "timestamp": [83.1, 84.88]}
188
+ ]
189
+ }
190
+ }
191
+ ```
192
+
193
+ Nynorsk:
194
+ ```json
195
+ {
196
+ {"text": "Nordmenn er nordlendingar, trøndarar, sørlendingar og folk frå alle andre regionar. Nordmenn er også innvandra frå Afghanistan, Pakistan, Polen, Sverige, Somalia og Syria. Det er ikkje alltid så lett å seie kvar vi er frå, kva nasjonalitet vi tilhøyrer. Det vi kallar heim, er der hjartet vårt er, og det kan ikkje alltid plasserast innanfor landegrenser. Nordmenn er jenter som er glad i jenter, gutar som erade i gutar, og jenter og gutar som er glade i kvarandre. Nordmenn trommar på Gud, Allah, Altet og ingenting. Nordmenn liker Grieg, Kygo, Helbiles og Kari Bremnes. Med andre ord, Noreg er dere! Noreg er oss. Mitt største håp for Noreg er at vi skal klare å ta vare på kvarandre, at vi skal byggje dette landet vidare på tillit, fellesskap og raushet."}
197
+ }
198
+ ```
199
+
200
+ English:
201
+ ```json
202
+ {
203
+ {"text": "Norwegians are Norwegians, trønders, southerners and people from all other regions. Norwegians are also invaded from Afghanistan, Pakistan, Poland, Sweden, Somalia and Suria. It is not always so easy to say where we are from, what nationality we belong to. What we call home is where our heart is, and it cannot always be placed within national borders. Norwegians are girls who like girls, boys who like boys, and girls and boys who like each other. Norwegians thrump on God, Allah, Altet and nothing. Norwegians like Grieg, Kygo, Helbilis and Kari Bremnes. In other words, Norway is you. Norway is us. My biggest hope for Norway is that we should be able to take care of each other, that we should build this country on trust, community and generosity."}
204
+ }
205
+ ```
206
+
207
+ </details>
208
+
209
+ ### Whisper CPP
210
+ Whisper CPP is a C++ implementation of the Whisper model, offering the same functionalities with the added benefits of C++ efficiency and performance optimizations. This allows embedding any Whisper model into a binary file, facilitating the development of real applications. However, it requires some familiarity with compiling C++ programs. Their [homepage](https://github.com/ggerganov/whisper.cpp) provides examples of how to build applications, including real-time transcription.
211
+
212
+ We have converted this model to the ggml-format model used by Whisper CPP binaries. The file can be downloaded [here](blob/main/ggml-model.bin), and a `q5_0` quantized version is also available [here](blob/main/ggml-model-q5_0.bin).
213
+
214
+ ```bash
215
+ # We can download and compile whisper.cpp
216
+ $ git clone --depth 1 https://github.com/ggerganov/whisper.cpp --branch v1.5.1
217
+ $ cd whisper.cpp/
218
+ $ make
219
+
220
+ # We also need to convert the audio to WAV as that is the only format supported by whisper.cpp
221
+ $ wget -N https://github.com/NbAiLab/nb-whisper/raw/main/audio/king.mp3
222
+ $ ffmpeg -i king.mp3 -ar 16000 -ac 1 -c:a pcm_s16le king.wav
223
+
224
+ # Lets download the two ggml-files from this site
225
+ wget -N https://huggingface.co/NbAiLabBeta/nb-whisper-tiny/resolve/main/ggml-model.bin -O models/nb-tiny-ggml-model.bin
226
+ wget -N https://huggingface.co/NbAiLabBeta/nb-whisper-tiny/resolve/main/ggml-model-q5_0.bin -O models/nb-tiny-ggml-model-q5_0.bin
227
+
228
+ # And run it with the f16 default model
229
+ $ ./main -l no -m models/nb-tiny-ggml-model.bin king.wav
230
+
231
+ # Or the quantized version
232
+ $ ./main -l no -m models/nb-tiny-ggml-model-q5_0.bin king.wav
233
+ ```
234
+
235
+ ### API
236
+ Instructions for accessing the models via a simple API are included in the demos under Spaces. Note that these demos are temporary and will only be available for a few weeks.
237
+
238
+ ## Training Data
239
+ The training data originates from Språkbanken and the National Library of Norway's digital collection, including:
240
+
241
+ - NST Norwegian ASR Database (16 kHz) and its corresponding dataset
242
+ - Transcribed speeches from the Norwegian Parliament by Språkbanken
243
+ - TV broadcast (NRK) subtitles (NLN digital collection)
244
+ - Audiobooks (NLN digital collection)
245
+
246
+ ## Downstream Use
247
+
248
+ The models, especially the smaller ones, may exhibit occasional hallucinations and may drop parts of the transcript. They are designed to convert spoken language into grammatically correct written sentences, which might not always be word-for-word translations. We have made two extra model variant for users that want a different transcription style. We encourage users to try the models themselves to get a better understanding.
249
+
250
+ ## Bias, Risks, and Limitations
251
+
252
+ Using these models without adequate risk assessment and mitigation could be considered irresponsible. They may contain biases or other undesirable distortions. Users who deploy these models or integrate them into systems or services are responsible for mitigating risks and complying with applicable AI regulations. The National Library of Norway, as the model owner, disclaims liability for any outcomes resulting from third-party use of these models.
253
+
254
+ ### Software
255
+ The model was trained using Jax/Flax and converted to PyTorch, Tensorflow, whisper.cpp, and ONXX formats. These are available under `Files and versions`. We welcome requests for conversion to other formats. All training code and scripts are released under the Apache License 2.0 in the GitHub repository [nb-whisper](https://github.com/NbAiLab/nb-whisper/).
256
+
257
+ ## Citation & Contributors
258
+ The NB-Whisper Tiny model is a product of the NoSTram project led by Per Egil Kummervold ([@pere](https://huggingface.co/pere)) at the National Library of Norway. Key contributors include Javier de la Rosa ([@versae](https://huggingface.co/versae)), Freddy Wetjen ([@freddyw](https://huggingface.co/freddyw)), and Rolv-Arild Braaten ([@Rolv-Arild](https://huggingface.co/Rolv-Arild)). NB AI-Lab, under the direction of Svein Arne Brygfjeld ([@Brygfjeld](https://huggingface.co/Brygfjeld)), supported the project's successful completion. A detailed paper on our process and findings is forthcoming.
259
+
260
+ ## Disclaimer
261
+
262
+ The models published in this repository are intended for a generalist purpose and are available to third parties. These models may have bias and/or any other undesirable distortions. When third parties, deploy or provide systems and/or services to other parties using any of these models (or using systems based on these models) or become users of the models, they should note that it is their responsibility to mitigate the risks arising from their use and, in any event, to comply with applicable regulations, including regulations regarding the use of artificial intelligence. In no event shall the owner of the models (The National Library of Norway) be liable for any results arising from the use made by third parties of these models.
263
+
264
+ ## Acknowledgements
265
+
266
+ Our gratitude extends to [Google TPU Research Cloud](https://sites.research.google/trc/about/) for training resources, Google Cloud for translation credits, and HuggingFace's Sanchit Ghandi for technical support. A special thank you to Per Erik Solberg at Språkbanken for the collaboration on the Stortinget corpus.
267
 
268
+ ## Contact
269
+ For feedback, technical concerns, or collaboration inquiries, please contact <a rel="noopener nofollow" href="mailto:ailab@nb.no">ailab@nb.no</a>. If you plan to include this model in your research, contact us for the latest information on our upcoming paper for citation purposes.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
config.json CHANGED
@@ -1,5 +1,5 @@
1
  {
2
- "_name_or_path": "NbAiLab/nb-whisper-tiny-v0.7",
3
  "activation_dropout": 0.1,
4
  "activation_function": "gelu",
5
  "apply_spec_augment": false,
 
1
  {
2
+ "_name_or_path": "./",
3
  "activation_dropout": 0.1,
4
  "activation_function": "gelu",
5
  "apply_spec_augment": false,
export_models.sh ADDED
@@ -0,0 +1,51 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ #!/bin/bash
2
+ pip install "optimum[exporters]>=1.14.1" tensorflow
3
+ git lfs track *.onnx*
4
+
5
+ python << END
6
+ from transformers import WhisperForConditionalGeneration, TFWhisperForConditionalGeneration, WhisperTokenizerFast
7
+ import shutil
8
+
9
+ # Backup generation_config.json
10
+ shutil.copyfile('./generation_config.json', './generation_config_backup.json')
11
+
12
+ print("Saving model to PyTorch...", end=" ")
13
+ model = WhisperForConditionalGeneration.from_pretrained("./", from_flax=True)
14
+ model.save_pretrained("./", safe_serialization=True)
15
+ model.save_pretrained("./")
16
+ print("Done.")
17
+
18
+ print("Saving model to TensorFlow...", end=" ")
19
+ tf_model = TFWhisperForConditionalGeneration.from_pretrained("./", from_pt=True)
20
+ tf_model.save_pretrained("./")
21
+ print("Done.")
22
+
23
+ # Restore the backup of generation_config.json
24
+ shutil.move('./generation_config_backup.json', './generation_config.json')
25
+
26
+ print("Saving model to ONNX...", end=" ")
27
+ from optimum.onnxruntime import ORTModelForSpeechSeq2Seq
28
+ ort_model = ORTModelForSpeechSeq2Seq.from_pretrained("./", export=True)
29
+ ort_model.save_pretrained("./onnx")
30
+ print("Done")
31
+
32
+ END
33
+
34
+ echo "Saving model to GGML (whisper.cpp)..."
35
+ wget -O convert-h5-to-ggml.py "https://raw.githubusercontent.com/ggerganov/whisper.cpp/94aa56f19eed8b2419bc5ede6b7fda85d5ca59be/models/convert-h5-to-ggml.py"
36
+ mkdir -p whisper/assets
37
+ wget -O whisper/assets/mel_filters.npz "https://github.com/openai/whisper/raw/c5d42560760a05584c1c79546a098287e5a771eb/whisper/assets/mel_filters.npz"
38
+ python ./convert-h5-to-ggml.py ./ ./ ./
39
+ rm ./convert-h5-to-ggml.py
40
+ rm -rf ./whisper
41
+ echo "Done"
42
+
43
+ echo "Quantizing GGML model..."
44
+ git clone --depth 1 https://github.com/ggerganov/whisper.cpp --branch v1.5.1
45
+ cd whisper.cpp/
46
+ make -j 32
47
+ make quantize -j 32
48
+ ./quantize ../ggml-model.bin ../ggml-model-q5_0.bin q5_0
49
+ cd ..
50
+ rm -rf whisper.cpp
51
+ echo "Done"
ggml-model-q5_0.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:56ca3ba7662b1d181360b7ea3ba2fbd90c7277d594cab4519ef521c2f46a7f37
3
+ size 29875738
ggml-model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6e266dd6819b80082cea339ccdb776a1d6fcc356259db7b6b1eb1ef3b650d340
3
+ size 77691730
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5ae3d5edf6dc478b370051e8378e11c4d7cbc3d6af55ce441dcb5345578a33c2
3
+ size 151061672
model_def.json ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "template_url": "https://raw.githubusercontent.com/NbAiLab/nb-whisper/main/template.md",
3
+ "replacements": {
4
+ "#Finetuned#": "# Finetuned Semantic model. \n\nThis model is trained 200 additional steps on top of the main model. The output from this model is less verbatim than when using the main model. The style might be more suited for instance for subtitling of videos since the goal is to use as few words as possible to express the essence of what is said.",
5
+ "#Size#": "Tiny",
6
+ "#size#": "tiny",
7
+ "#model_name#": "NbAiLabBeta/nb-whisper-tiny-semantic"
8
+ }
9
+ }
onnx/added_tokens.json ADDED
@@ -0,0 +1,1609 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "<|0.00|>": 50364,
3
+ "<|0.02|>": 50365,
4
+ "<|0.04|>": 50366,
5
+ "<|0.06|>": 50367,
6
+ "<|0.08|>": 50368,
7
+ "<|0.10|>": 50369,
8
+ "<|0.12|>": 50370,
9
+ "<|0.14|>": 50371,
10
+ "<|0.16|>": 50372,
11
+ "<|0.18|>": 50373,
12
+ "<|0.20|>": 50374,
13
+ "<|0.22|>": 50375,
14
+ "<|0.24|>": 50376,
15
+ "<|0.26|>": 50377,
16
+ "<|0.28|>": 50378,
17
+ "<|0.30|>": 50379,
18
+ "<|0.32|>": 50380,
19
+ "<|0.34|>": 50381,
20
+ "<|0.36|>": 50382,
21
+ "<|0.38|>": 50383,
22
+ "<|0.40|>": 50384,
23
+ "<|0.42|>": 50385,
24
+ "<|0.44|>": 50386,
25
+ "<|0.46|>": 50387,
26
+ "<|0.48|>": 50388,
27
+ "<|0.50|>": 50389,
28
+ "<|0.52|>": 50390,
29
+ "<|0.54|>": 50391,
30
+ "<|0.56|>": 50392,
31
+ "<|0.58|>": 50393,
32
+ "<|0.60|>": 50394,
33
+ "<|0.62|>": 50395,
34
+ "<|0.64|>": 50396,
35
+ "<|0.66|>": 50397,
36
+ "<|0.68|>": 50398,
37
+ "<|0.70|>": 50399,
38
+ "<|0.72|>": 50400,
39
+ "<|0.74|>": 50401,
40
+ "<|0.76|>": 50402,
41
+ "<|0.78|>": 50403,
42
+ "<|0.80|>": 50404,
43
+ "<|0.82|>": 50405,
44
+ "<|0.84|>": 50406,
45
+ "<|0.86|>": 50407,
46
+ "<|0.88|>": 50408,
47
+ "<|0.90|>": 50409,
48
+ "<|0.92|>": 50410,
49
+ "<|0.94|>": 50411,
50
+ "<|0.96|>": 50412,
51
+ "<|0.98|>": 50413,
52
+ "<|1.00|>": 50414,
53
+ "<|1.02|>": 50415,
54
+ "<|1.04|>": 50416,
55
+ "<|1.06|>": 50417,
56
+ "<|1.08|>": 50418,
57
+ "<|1.10|>": 50419,
58
+ "<|1.12|>": 50420,
59
+ "<|1.14|>": 50421,
60
+ "<|1.16|>": 50422,
61
+ "<|1.18|>": 50423,
62
+ "<|1.20|>": 50424,
63
+ "<|1.22|>": 50425,
64
+ "<|1.24|>": 50426,
65
+ "<|1.26|>": 50427,
66
+ "<|1.28|>": 50428,
67
+ "<|1.30|>": 50429,
68
+ "<|1.32|>": 50430,
69
+ "<|1.34|>": 50431,
70
+ "<|1.36|>": 50432,
71
+ "<|1.38|>": 50433,
72
+ "<|1.40|>": 50434,
73
+ "<|1.42|>": 50435,
74
+ "<|1.44|>": 50436,
75
+ "<|1.46|>": 50437,
76
+ "<|1.48|>": 50438,
77
+ "<|1.50|>": 50439,
78
+ "<|1.52|>": 50440,
79
+ "<|1.54|>": 50441,
80
+ "<|1.56|>": 50442,
81
+ "<|1.58|>": 50443,
82
+ "<|1.60|>": 50444,
83
+ "<|1.62|>": 50445,
84
+ "<|1.64|>": 50446,
85
+ "<|1.66|>": 50447,
86
+ "<|1.68|>": 50448,
87
+ "<|1.70|>": 50449,
88
+ "<|1.72|>": 50450,
89
+ "<|1.74|>": 50451,
90
+ "<|1.76|>": 50452,
91
+ "<|1.78|>": 50453,
92
+ "<|1.80|>": 50454,
93
+ "<|1.82|>": 50455,
94
+ "<|1.84|>": 50456,
95
+ "<|1.86|>": 50457,
96
+ "<|1.88|>": 50458,
97
+ "<|1.90|>": 50459,
98
+ "<|1.92|>": 50460,
99
+ "<|1.94|>": 50461,
100
+ "<|1.96|>": 50462,
101
+ "<|1.98|>": 50463,
102
+ "<|10.00|>": 50864,
103
+ "<|10.02|>": 50865,
104
+ "<|10.04|>": 50866,
105
+ "<|10.06|>": 50867,
106
+ "<|10.08|>": 50868,
107
+ "<|10.10|>": 50869,
108
+ "<|10.12|>": 50870,
109
+ "<|10.14|>": 50871,
110
+ "<|10.16|>": 50872,
111
+ "<|10.18|>": 50873,
112
+ "<|10.20|>": 50874,
113
+ "<|10.22|>": 50875,
114
+ "<|10.24|>": 50876,
115
+ "<|10.26|>": 50877,
116
+ "<|10.28|>": 50878,
117
+ "<|10.30|>": 50879,
118
+ "<|10.32|>": 50880,
119
+ "<|10.34|>": 50881,
120
+ "<|10.36|>": 50882,
121
+ "<|10.38|>": 50883,
122
+ "<|10.40|>": 50884,
123
+ "<|10.42|>": 50885,
124
+ "<|10.44|>": 50886,
125
+ "<|10.46|>": 50887,
126
+ "<|10.48|>": 50888,
127
+ "<|10.50|>": 50889,
128
+ "<|10.52|>": 50890,
129
+ "<|10.54|>": 50891,
130
+ "<|10.56|>": 50892,
131
+ "<|10.58|>": 50893,
132
+ "<|10.60|>": 50894,
133
+ "<|10.62|>": 50895,
134
+ "<|10.64|>": 50896,
135
+ "<|10.66|>": 50897,
136
+ "<|10.68|>": 50898,
137
+ "<|10.70|>": 50899,
138
+ "<|10.72|>": 50900,
139
+ "<|10.74|>": 50901,
140
+ "<|10.76|>": 50902,
141
+ "<|10.78|>": 50903,
142
+ "<|10.80|>": 50904,
143
+ "<|10.82|>": 50905,
144
+ "<|10.84|>": 50906,
145
+ "<|10.86|>": 50907,
146
+ "<|10.88|>": 50908,
147
+ "<|10.90|>": 50909,
148
+ "<|10.92|>": 50910,
149
+ "<|10.94|>": 50911,
150
+ "<|10.96|>": 50912,
151
+ "<|10.98|>": 50913,
152
+ "<|11.00|>": 50914,
153
+ "<|11.02|>": 50915,
154
+ "<|11.04|>": 50916,
155
+ "<|11.06|>": 50917,
156
+ "<|11.08|>": 50918,
157
+ "<|11.10|>": 50919,
158
+ "<|11.12|>": 50920,
159
+ "<|11.14|>": 50921,
160
+ "<|11.16|>": 50922,
161
+ "<|11.18|>": 50923,
162
+ "<|11.20|>": 50924,
163
+ "<|11.22|>": 50925,
164
+ "<|11.24|>": 50926,
165
+ "<|11.26|>": 50927,
166
+ "<|11.28|>": 50928,
167
+ "<|11.30|>": 50929,
168
+ "<|11.32|>": 50930,
169
+ "<|11.34|>": 50931,
170
+ "<|11.36|>": 50932,
171
+ "<|11.38|>": 50933,
172
+ "<|11.40|>": 50934,
173
+ "<|11.42|>": 50935,
174
+ "<|11.44|>": 50936,
175
+ "<|11.46|>": 50937,
176
+ "<|11.48|>": 50938,
177
+ "<|11.50|>": 50939,
178
+ "<|11.52|>": 50940,
179
+ "<|11.54|>": 50941,
180
+ "<|11.56|>": 50942,
181
+ "<|11.58|>": 50943,
182
+ "<|11.60|>": 50944,
183
+ "<|11.62|>": 50945,
184
+ "<|11.64|>": 50946,
185
+ "<|11.66|>": 50947,
186
+ "<|11.68|>": 50948,
187
+ "<|11.70|>": 50949,
188
+ "<|11.72|>": 50950,
189
+ "<|11.74|>": 50951,
190
+ "<|11.76|>": 50952,
191
+ "<|11.78|>": 50953,
192
+ "<|11.80|>": 50954,
193
+ "<|11.82|>": 50955,
194
+ "<|11.84|>": 50956,
195
+ "<|11.86|>": 50957,
196
+ "<|11.88|>": 50958,
197
+ "<|11.90|>": 50959,
198
+ "<|11.92|>": 50960,
199
+ "<|11.94|>": 50961,
200
+ "<|11.96|>": 50962,
201
+ "<|11.98|>": 50963,
202
+ "<|12.00|>": 50964,
203
+ "<|12.02|>": 50965,
204
+ "<|12.04|>": 50966,
205
+ "<|12.06|>": 50967,
206
+ "<|12.08|>": 50968,
207
+ "<|12.10|>": 50969,
208
+ "<|12.12|>": 50970,
209
+ "<|12.14|>": 50971,
210
+ "<|12.16|>": 50972,
211
+ "<|12.18|>": 50973,
212
+ "<|12.20|>": 50974,
213
+ "<|12.22|>": 50975,
214
+ "<|12.24|>": 50976,
215
+ "<|12.26|>": 50977,
216
+ "<|12.28|>": 50978,
217
+ "<|12.30|>": 50979,
218
+ "<|12.32|>": 50980,
219
+ "<|12.34|>": 50981,
220
+ "<|12.36|>": 50982,
221
+ "<|12.38|>": 50983,
222
+ "<|12.40|>": 50984,
223
+ "<|12.42|>": 50985,
224
+ "<|12.44|>": 50986,
225
+ "<|12.46|>": 50987,
226
+ "<|12.48|>": 50988,
227
+ "<|12.50|>": 50989,
228
+ "<|12.52|>": 50990,
229
+ "<|12.54|>": 50991,
230
+ "<|12.56|>": 50992,
231
+ "<|12.58|>": 50993,
232
+ "<|12.60|>": 50994,
233
+ "<|12.62|>": 50995,
234
+ "<|12.64|>": 50996,
235
+ "<|12.66|>": 50997,
236
+ "<|12.68|>": 50998,
237
+ "<|12.70|>": 50999,
238
+ "<|12.72|>": 51000,
239
+ "<|12.74|>": 51001,
240
+ "<|12.76|>": 51002,
241
+ "<|12.78|>": 51003,
242
+ "<|12.80|>": 51004,
243
+ "<|12.82|>": 51005,
244
+ "<|12.84|>": 51006,
245
+ "<|12.86|>": 51007,
246
+ "<|12.88|>": 51008,
247
+ "<|12.90|>": 51009,
248
+ "<|12.92|>": 51010,
249
+ "<|12.94|>": 51011,
250
+ "<|12.96|>": 51012,
251
+ "<|12.98|>": 51013,
252
+ "<|13.00|>": 51014,
253
+ "<|13.02|>": 51015,
254
+ "<|13.04|>": 51016,
255
+ "<|13.06|>": 51017,
256
+ "<|13.08|>": 51018,
257
+ "<|13.10|>": 51019,
258
+ "<|13.12|>": 51020,
259
+ "<|13.14|>": 51021,
260
+ "<|13.16|>": 51022,
261
+ "<|13.18|>": 51023,
262
+ "<|13.20|>": 51024,
263
+ "<|13.22|>": 51025,
264
+ "<|13.24|>": 51026,
265
+ "<|13.26|>": 51027,
266
+ "<|13.28|>": 51028,
267
+ "<|13.30|>": 51029,
268
+ "<|13.32|>": 51030,
269
+ "<|13.34|>": 51031,
270
+ "<|13.36|>": 51032,
271
+ "<|13.38|>": 51033,
272
+ "<|13.40|>": 51034,
273
+ "<|13.42|>": 51035,
274
+ "<|13.44|>": 51036,
275
+ "<|13.46|>": 51037,
276
+ "<|13.48|>": 51038,
277
+ "<|13.50|>": 51039,
278
+ "<|13.52|>": 51040,
279
+ "<|13.54|>": 51041,
280
+ "<|13.56|>": 51042,
281
+ "<|13.58|>": 51043,
282
+ "<|13.60|>": 51044,
283
+ "<|13.62|>": 51045,
284
+ "<|13.64|>": 51046,
285
+ "<|13.66|>": 51047,
286
+ "<|13.68|>": 51048,
287
+ "<|13.70|>": 51049,
288
+ "<|13.72|>": 51050,
289
+ "<|13.74|>": 51051,
290
+ "<|13.76|>": 51052,
291
+ "<|13.78|>": 51053,
292
+ "<|13.80|>": 51054,
293
+ "<|13.82|>": 51055,
294
+ "<|13.84|>": 51056,
295
+ "<|13.86|>": 51057,
296
+ "<|13.88|>": 51058,
297
+ "<|13.90|>": 51059,
298
+ "<|13.92|>": 51060,
299
+ "<|13.94|>": 51061,
300
+ "<|13.96|>": 51062,
301
+ "<|13.98|>": 51063,
302
+ "<|14.00|>": 51064,
303
+ "<|14.02|>": 51065,
304
+ "<|14.04|>": 51066,
305
+ "<|14.06|>": 51067,
306
+ "<|14.08|>": 51068,
307
+ "<|14.10|>": 51069,
308
+ "<|14.12|>": 51070,
309
+ "<|14.14|>": 51071,
310
+ "<|14.16|>": 51072,
311
+ "<|14.18|>": 51073,
312
+ "<|14.20|>": 51074,
313
+ "<|14.22|>": 51075,
314
+ "<|14.24|>": 51076,
315
+ "<|14.26|>": 51077,
316
+ "<|14.28|>": 51078,
317
+ "<|14.30|>": 51079,
318
+ "<|14.32|>": 51080,
319
+ "<|14.34|>": 51081,
320
+ "<|14.36|>": 51082,
321
+ "<|14.38|>": 51083,
322
+ "<|14.40|>": 51084,
323
+ "<|14.42|>": 51085,
324
+ "<|14.44|>": 51086,
325
+ "<|14.46|>": 51087,
326
+ "<|14.48|>": 51088,
327
+ "<|14.50|>": 51089,
328
+ "<|14.52|>": 51090,
329
+ "<|14.54|>": 51091,
330
+ "<|14.56|>": 51092,
331
+ "<|14.58|>": 51093,
332
+ "<|14.60|>": 51094,
333
+ "<|14.62|>": 51095,
334
+ "<|14.64|>": 51096,
335
+ "<|14.66|>": 51097,
336
+ "<|14.68|>": 51098,
337
+ "<|14.70|>": 51099,
338
+ "<|14.72|>": 51100,
339
+ "<|14.74|>": 51101,
340
+ "<|14.76|>": 51102,
341
+ "<|14.78|>": 51103,
342
+ "<|14.80|>": 51104,
343
+ "<|14.82|>": 51105,
344
+ "<|14.84|>": 51106,
345
+ "<|14.86|>": 51107,
346
+ "<|14.88|>": 51108,
347
+ "<|14.90|>": 51109,
348
+ "<|14.92|>": 51110,
349
+ "<|14.94|>": 51111,
350
+ "<|14.96|>": 51112,
351
+ "<|14.98|>": 51113,
352
+ "<|15.00|>": 51114,
353
+ "<|15.02|>": 51115,
354
+ "<|15.04|>": 51116,
355
+ "<|15.06|>": 51117,
356
+ "<|15.08|>": 51118,
357
+ "<|15.10|>": 51119,
358
+ "<|15.12|>": 51120,
359
+ "<|15.14|>": 51121,
360
+ "<|15.16|>": 51122,
361
+ "<|15.18|>": 51123,
362
+ "<|15.20|>": 51124,
363
+ "<|15.22|>": 51125,
364
+ "<|15.24|>": 51126,
365
+ "<|15.26|>": 51127,
366
+ "<|15.28|>": 51128,
367
+ "<|15.30|>": 51129,
368
+ "<|15.32|>": 51130,
369
+ "<|15.34|>": 51131,
370
+ "<|15.36|>": 51132,
371
+ "<|15.38|>": 51133,
372
+ "<|15.40|>": 51134,
373
+ "<|15.42|>": 51135,
374
+ "<|15.44|>": 51136,
375
+ "<|15.46|>": 51137,
376
+ "<|15.48|>": 51138,
377
+ "<|15.50|>": 51139,
378
+ "<|15.52|>": 51140,
379
+ "<|15.54|>": 51141,
380
+ "<|15.56|>": 51142,
381
+ "<|15.58|>": 51143,
382
+ "<|15.60|>": 51144,
383
+ "<|15.62|>": 51145,
384
+ "<|15.64|>": 51146,
385
+ "<|15.66|>": 51147,
386
+ "<|15.68|>": 51148,
387
+ "<|15.70|>": 51149,
388
+ "<|15.72|>": 51150,
389
+ "<|15.74|>": 51151,
390
+ "<|15.76|>": 51152,
391
+ "<|15.78|>": 51153,
392
+ "<|15.80|>": 51154,
393
+ "<|15.82|>": 51155,
394
+ "<|15.84|>": 51156,
395
+ "<|15.86|>": 51157,
396
+ "<|15.88|>": 51158,
397
+ "<|15.90|>": 51159,
398
+ "<|15.92|>": 51160,
399
+ "<|15.94|>": 51161,
400
+ "<|15.96|>": 51162,
401
+ "<|15.98|>": 51163,
402
+ "<|16.00|>": 51164,
403
+ "<|16.02|>": 51165,
404
+ "<|16.04|>": 51166,
405
+ "<|16.06|>": 51167,
406
+ "<|16.08|>": 51168,
407
+ "<|16.10|>": 51169,
408
+ "<|16.12|>": 51170,
409
+ "<|16.14|>": 51171,
410
+ "<|16.16|>": 51172,
411
+ "<|16.18|>": 51173,
412
+ "<|16.20|>": 51174,
413
+ "<|16.22|>": 51175,
414
+ "<|16.24|>": 51176,
415
+ "<|16.26|>": 51177,
416
+ "<|16.28|>": 51178,
417
+ "<|16.30|>": 51179,
418
+ "<|16.32|>": 51180,
419
+ "<|16.34|>": 51181,
420
+ "<|16.36|>": 51182,
421
+ "<|16.38|>": 51183,
422
+ "<|16.40|>": 51184,
423
+ "<|16.42|>": 51185,
424
+ "<|16.44|>": 51186,
425
+ "<|16.46|>": 51187,
426
+ "<|16.48|>": 51188,
427
+ "<|16.50|>": 51189,
428
+ "<|16.52|>": 51190,
429
+ "<|16.54|>": 51191,
430
+ "<|16.56|>": 51192,
431
+ "<|16.58|>": 51193,
432
+ "<|16.60|>": 51194,
433
+ "<|16.62|>": 51195,
434
+ "<|16.64|>": 51196,
435
+ "<|16.66|>": 51197,
436
+ "<|16.68|>": 51198,
437
+ "<|16.70|>": 51199,
438
+ "<|16.72|>": 51200,
439
+ "<|16.74|>": 51201,
440
+ "<|16.76|>": 51202,
441
+ "<|16.78|>": 51203,
442
+ "<|16.80|>": 51204,
443
+ "<|16.82|>": 51205,
444
+ "<|16.84|>": 51206,
445
+ "<|16.86|>": 51207,
446
+ "<|16.88|>": 51208,
447
+ "<|16.90|>": 51209,
448
+ "<|16.92|>": 51210,
449
+ "<|16.94|>": 51211,
450
+ "<|16.96|>": 51212,
451
+ "<|16.98|>": 51213,
452
+ "<|17.00|>": 51214,
453
+ "<|17.02|>": 51215,
454
+ "<|17.04|>": 51216,
455
+ "<|17.06|>": 51217,
456
+ "<|17.08|>": 51218,
457
+ "<|17.10|>": 51219,
458
+ "<|17.12|>": 51220,
459
+ "<|17.14|>": 51221,
460
+ "<|17.16|>": 51222,
461
+ "<|17.18|>": 51223,
462
+ "<|17.20|>": 51224,
463
+ "<|17.22|>": 51225,
464
+ "<|17.24|>": 51226,
465
+ "<|17.26|>": 51227,
466
+ "<|17.28|>": 51228,
467
+ "<|17.30|>": 51229,
468
+ "<|17.32|>": 51230,
469
+ "<|17.34|>": 51231,
470
+ "<|17.36|>": 51232,
471
+ "<|17.38|>": 51233,
472
+ "<|17.40|>": 51234,
473
+ "<|17.42|>": 51235,
474
+ "<|17.44|>": 51236,
475
+ "<|17.46|>": 51237,
476
+ "<|17.48|>": 51238,
477
+ "<|17.50|>": 51239,
478
+ "<|17.52|>": 51240,
479
+ "<|17.54|>": 51241,
480
+ "<|17.56|>": 51242,
481
+ "<|17.58|>": 51243,
482
+ "<|17.60|>": 51244,
483
+ "<|17.62|>": 51245,
484
+ "<|17.64|>": 51246,
485
+ "<|17.66|>": 51247,
486
+ "<|17.68|>": 51248,
487
+ "<|17.70|>": 51249,
488
+ "<|17.72|>": 51250,
489
+ "<|17.74|>": 51251,
490
+ "<|17.76|>": 51252,
491
+ "<|17.78|>": 51253,
492
+ "<|17.80|>": 51254,
493
+ "<|17.82|>": 51255,
494
+ "<|17.84|>": 51256,
495
+ "<|17.86|>": 51257,
496
+ "<|17.88|>": 51258,
497
+ "<|17.90|>": 51259,
498
+ "<|17.92|>": 51260,
499
+ "<|17.94|>": 51261,
500
+ "<|17.96|>": 51262,
501
+ "<|17.98|>": 51263,
502
+ "<|18.00|>": 51264,
503
+ "<|18.02|>": 51265,
504
+ "<|18.04|>": 51266,
505
+ "<|18.06|>": 51267,
506
+ "<|18.08|>": 51268,
507
+ "<|18.10|>": 51269,
508
+ "<|18.12|>": 51270,
509
+ "<|18.14|>": 51271,
510
+ "<|18.16|>": 51272,
511
+ "<|18.18|>": 51273,
512
+ "<|18.20|>": 51274,
513
+ "<|18.22|>": 51275,
514
+ "<|18.24|>": 51276,
515
+ "<|18.26|>": 51277,
516
+ "<|18.28|>": 51278,
517
+ "<|18.30|>": 51279,
518
+ "<|18.32|>": 51280,
519
+ "<|18.34|>": 51281,
520
+ "<|18.36|>": 51282,
521
+ "<|18.38|>": 51283,
522
+ "<|18.40|>": 51284,
523
+ "<|18.42|>": 51285,
524
+ "<|18.44|>": 51286,
525
+ "<|18.46|>": 51287,
526
+ "<|18.48|>": 51288,
527
+ "<|18.50|>": 51289,
528
+ "<|18.52|>": 51290,
529
+ "<|18.54|>": 51291,
530
+ "<|18.56|>": 51292,
531
+ "<|18.58|>": 51293,
532
+ "<|18.60|>": 51294,
533
+ "<|18.62|>": 51295,
534
+ "<|18.64|>": 51296,
535
+ "<|18.66|>": 51297,
536
+ "<|18.68|>": 51298,
537
+ "<|18.70|>": 51299,
538
+ "<|18.72|>": 51300,
539
+ "<|18.74|>": 51301,
540
+ "<|18.76|>": 51302,
541
+ "<|18.78|>": 51303,
542
+ "<|18.80|>": 51304,
543
+ "<|18.82|>": 51305,
544
+ "<|18.84|>": 51306,
545
+ "<|18.86|>": 51307,
546
+ "<|18.88|>": 51308,
547
+ "<|18.90|>": 51309,
548
+ "<|18.92|>": 51310,
549
+ "<|18.94|>": 51311,
550
+ "<|18.96|>": 51312,
551
+ "<|18.98|>": 51313,
552
+ "<|19.00|>": 51314,
553
+ "<|19.02|>": 51315,
554
+ "<|19.04|>": 51316,
555
+ "<|19.06|>": 51317,
556
+ "<|19.08|>": 51318,
557
+ "<|19.10|>": 51319,
558
+ "<|19.12|>": 51320,
559
+ "<|19.14|>": 51321,
560
+ "<|19.16|>": 51322,
561
+ "<|19.18|>": 51323,
562
+ "<|19.20|>": 51324,
563
+ "<|19.22|>": 51325,
564
+ "<|19.24|>": 51326,
565
+ "<|19.26|>": 51327,
566
+ "<|19.28|>": 51328,
567
+ "<|19.30|>": 51329,
568
+ "<|19.32|>": 51330,
569
+ "<|19.34|>": 51331,
570
+ "<|19.36|>": 51332,
571
+ "<|19.38|>": 51333,
572
+ "<|19.40|>": 51334,
573
+ "<|19.42|>": 51335,
574
+ "<|19.44|>": 51336,
575
+ "<|19.46|>": 51337,
576
+ "<|19.48|>": 51338,
577
+ "<|19.50|>": 51339,
578
+ "<|19.52|>": 51340,
579
+ "<|19.54|>": 51341,
580
+ "<|19.56|>": 51342,
581
+ "<|19.58|>": 51343,
582
+ "<|19.60|>": 51344,
583
+ "<|19.62|>": 51345,
584
+ "<|19.64|>": 51346,
585
+ "<|19.66|>": 51347,
586
+ "<|19.68|>": 51348,
587
+ "<|19.70|>": 51349,
588
+ "<|19.72|>": 51350,
589
+ "<|19.74|>": 51351,
590
+ "<|19.76|>": 51352,
591
+ "<|19.78|>": 51353,
592
+ "<|19.80|>": 51354,
593
+ "<|19.82|>": 51355,
594
+ "<|19.84|>": 51356,
595
+ "<|19.86|>": 51357,
596
+ "<|19.88|>": 51358,
597
+ "<|19.90|>": 51359,
598
+ "<|19.92|>": 51360,
599
+ "<|19.94|>": 51361,
600
+ "<|19.96|>": 51362,
601
+ "<|19.98|>": 51363,
602
+ "<|2.00|>": 50464,
603
+ "<|2.02|>": 50465,
604
+ "<|2.04|>": 50466,
605
+ "<|2.06|>": 50467,
606
+ "<|2.08|>": 50468,
607
+ "<|2.10|>": 50469,
608
+ "<|2.12|>": 50470,
609
+ "<|2.14|>": 50471,
610
+ "<|2.16|>": 50472,
611
+ "<|2.18|>": 50473,
612
+ "<|2.20|>": 50474,
613
+ "<|2.22|>": 50475,
614
+ "<|2.24|>": 50476,
615
+ "<|2.26|>": 50477,
616
+ "<|2.28|>": 50478,
617
+ "<|2.30|>": 50479,
618
+ "<|2.32|>": 50480,
619
+ "<|2.34|>": 50481,
620
+ "<|2.36|>": 50482,
621
+ "<|2.38|>": 50483,
622
+ "<|2.40|>": 50484,
623
+ "<|2.42|>": 50485,
624
+ "<|2.44|>": 50486,
625
+ "<|2.46|>": 50487,
626
+ "<|2.48|>": 50488,
627
+ "<|2.50|>": 50489,
628
+ "<|2.52|>": 50490,
629
+ "<|2.54|>": 50491,
630
+ "<|2.56|>": 50492,
631
+ "<|2.58|>": 50493,
632
+ "<|2.60|>": 50494,
633
+ "<|2.62|>": 50495,
634
+ "<|2.64|>": 50496,
635
+ "<|2.66|>": 50497,
636
+ "<|2.68|>": 50498,
637
+ "<|2.70|>": 50499,
638
+ "<|2.72|>": 50500,
639
+ "<|2.74|>": 50501,
640
+ "<|2.76|>": 50502,
641
+ "<|2.78|>": 50503,
642
+ "<|2.80|>": 50504,
643
+ "<|2.82|>": 50505,
644
+ "<|2.84|>": 50506,
645
+ "<|2.86|>": 50507,
646
+ "<|2.88|>": 50508,
647
+ "<|2.90|>": 50509,
648
+ "<|2.92|>": 50510,
649
+ "<|2.94|>": 50511,
650
+ "<|2.96|>": 50512,
651
+ "<|2.98|>": 50513,
652
+ "<|20.00|>": 51364,
653
+ "<|20.02|>": 51365,
654
+ "<|20.04|>": 51366,
655
+ "<|20.06|>": 51367,
656
+ "<|20.08|>": 51368,
657
+ "<|20.10|>": 51369,
658
+ "<|20.12|>": 51370,
659
+ "<|20.14|>": 51371,
660
+ "<|20.16|>": 51372,
661
+ "<|20.18|>": 51373,
662
+ "<|20.20|>": 51374,
663
+ "<|20.22|>": 51375,
664
+ "<|20.24|>": 51376,
665
+ "<|20.26|>": 51377,
666
+ "<|20.28|>": 51378,
667
+ "<|20.30|>": 51379,
668
+ "<|20.32|>": 51380,
669
+ "<|20.34|>": 51381,
670
+ "<|20.36|>": 51382,
671
+ "<|20.38|>": 51383,
672
+ "<|20.40|>": 51384,
673
+ "<|20.42|>": 51385,
674
+ "<|20.44|>": 51386,
675
+ "<|20.46|>": 51387,
676
+ "<|20.48|>": 51388,
677
+ "<|20.50|>": 51389,
678
+ "<|20.52|>": 51390,
679
+ "<|20.54|>": 51391,
680
+ "<|20.56|>": 51392,
681
+ "<|20.58|>": 51393,
682
+ "<|20.60|>": 51394,
683
+ "<|20.62|>": 51395,
684
+ "<|20.64|>": 51396,
685
+ "<|20.66|>": 51397,
686
+ "<|20.68|>": 51398,
687
+ "<|20.70|>": 51399,
688
+ "<|20.72|>": 51400,
689
+ "<|20.74|>": 51401,
690
+ "<|20.76|>": 51402,
691
+ "<|20.78|>": 51403,
692
+ "<|20.80|>": 51404,
693
+ "<|20.82|>": 51405,
694
+ "<|20.84|>": 51406,
695
+ "<|20.86|>": 51407,
696
+ "<|20.88|>": 51408,
697
+ "<|20.90|>": 51409,
698
+ "<|20.92|>": 51410,
699
+ "<|20.94|>": 51411,
700
+ "<|20.96|>": 51412,
701
+ "<|20.98|>": 51413,
702
+ "<|21.00|>": 51414,
703
+ "<|21.02|>": 51415,
704
+ "<|21.04|>": 51416,
705
+ "<|21.06|>": 51417,
706
+ "<|21.08|>": 51418,
707
+ "<|21.10|>": 51419,
708
+ "<|21.12|>": 51420,
709
+ "<|21.14|>": 51421,
710
+ "<|21.16|>": 51422,
711
+ "<|21.18|>": 51423,
712
+ "<|21.20|>": 51424,
713
+ "<|21.22|>": 51425,
714
+ "<|21.24|>": 51426,
715
+ "<|21.26|>": 51427,
716
+ "<|21.28|>": 51428,
717
+ "<|21.30|>": 51429,
718
+ "<|21.32|>": 51430,
719
+ "<|21.34|>": 51431,
720
+ "<|21.36|>": 51432,
721
+ "<|21.38|>": 51433,
722
+ "<|21.40|>": 51434,
723
+ "<|21.42|>": 51435,
724
+ "<|21.44|>": 51436,
725
+ "<|21.46|>": 51437,
726
+ "<|21.48|>": 51438,
727
+ "<|21.50|>": 51439,
728
+ "<|21.52|>": 51440,
729
+ "<|21.54|>": 51441,
730
+ "<|21.56|>": 51442,
731
+ "<|21.58|>": 51443,
732
+ "<|21.60|>": 51444,
733
+ "<|21.62|>": 51445,
734
+ "<|21.64|>": 51446,
735
+ "<|21.66|>": 51447,
736
+ "<|21.68|>": 51448,
737
+ "<|21.70|>": 51449,
738
+ "<|21.72|>": 51450,
739
+ "<|21.74|>": 51451,
740
+ "<|21.76|>": 51452,
741
+ "<|21.78|>": 51453,
742
+ "<|21.80|>": 51454,
743
+ "<|21.82|>": 51455,
744
+ "<|21.84|>": 51456,
745
+ "<|21.86|>": 51457,
746
+ "<|21.88|>": 51458,
747
+ "<|21.90|>": 51459,
748
+ "<|21.92|>": 51460,
749
+ "<|21.94|>": 51461,
750
+ "<|21.96|>": 51462,
751
+ "<|21.98|>": 51463,
752
+ "<|22.00|>": 51464,
753
+ "<|22.02|>": 51465,
754
+ "<|22.04|>": 51466,
755
+ "<|22.06|>": 51467,
756
+ "<|22.08|>": 51468,
757
+ "<|22.10|>": 51469,
758
+ "<|22.12|>": 51470,
759
+ "<|22.14|>": 51471,
760
+ "<|22.16|>": 51472,
761
+ "<|22.18|>": 51473,
762
+ "<|22.20|>": 51474,
763
+ "<|22.22|>": 51475,
764
+ "<|22.24|>": 51476,
765
+ "<|22.26|>": 51477,
766
+ "<|22.28|>": 51478,
767
+ "<|22.30|>": 51479,
768
+ "<|22.32|>": 51480,
769
+ "<|22.34|>": 51481,
770
+ "<|22.36|>": 51482,
771
+ "<|22.38|>": 51483,
772
+ "<|22.40|>": 51484,
773
+ "<|22.42|>": 51485,
774
+ "<|22.44|>": 51486,
775
+ "<|22.46|>": 51487,
776
+ "<|22.48|>": 51488,
777
+ "<|22.50|>": 51489,
778
+ "<|22.52|>": 51490,
779
+ "<|22.54|>": 51491,
780
+ "<|22.56|>": 51492,
781
+ "<|22.58|>": 51493,
782
+ "<|22.60|>": 51494,
783
+ "<|22.62|>": 51495,
784
+ "<|22.64|>": 51496,
785
+ "<|22.66|>": 51497,
786
+ "<|22.68|>": 51498,
787
+ "<|22.70|>": 51499,
788
+ "<|22.72|>": 51500,
789
+ "<|22.74|>": 51501,
790
+ "<|22.76|>": 51502,
791
+ "<|22.78|>": 51503,
792
+ "<|22.80|>": 51504,
793
+ "<|22.82|>": 51505,
794
+ "<|22.84|>": 51506,
795
+ "<|22.86|>": 51507,
796
+ "<|22.88|>": 51508,
797
+ "<|22.90|>": 51509,
798
+ "<|22.92|>": 51510,
799
+ "<|22.94|>": 51511,
800
+ "<|22.96|>": 51512,
801
+ "<|22.98|>": 51513,
802
+ "<|23.00|>": 51514,
803
+ "<|23.02|>": 51515,
804
+ "<|23.04|>": 51516,
805
+ "<|23.06|>": 51517,
806
+ "<|23.08|>": 51518,
807
+ "<|23.10|>": 51519,
808
+ "<|23.12|>": 51520,
809
+ "<|23.14|>": 51521,
810
+ "<|23.16|>": 51522,
811
+ "<|23.18|>": 51523,
812
+ "<|23.20|>": 51524,
813
+ "<|23.22|>": 51525,
814
+ "<|23.24|>": 51526,
815
+ "<|23.26|>": 51527,
816
+ "<|23.28|>": 51528,
817
+ "<|23.30|>": 51529,
818
+ "<|23.32|>": 51530,
819
+ "<|23.34|>": 51531,
820
+ "<|23.36|>": 51532,
821
+ "<|23.38|>": 51533,
822
+ "<|23.40|>": 51534,
823
+ "<|23.42|>": 51535,
824
+ "<|23.44|>": 51536,
825
+ "<|23.46|>": 51537,
826
+ "<|23.48|>": 51538,
827
+ "<|23.50|>": 51539,
828
+ "<|23.52|>": 51540,
829
+ "<|23.54|>": 51541,
830
+ "<|23.56|>": 51542,
831
+ "<|23.58|>": 51543,
832
+ "<|23.60|>": 51544,
833
+ "<|23.62|>": 51545,
834
+ "<|23.64|>": 51546,
835
+ "<|23.66|>": 51547,
836
+ "<|23.68|>": 51548,
837
+ "<|23.70|>": 51549,
838
+ "<|23.72|>": 51550,
839
+ "<|23.74|>": 51551,
840
+ "<|23.76|>": 51552,
841
+ "<|23.78|>": 51553,
842
+ "<|23.80|>": 51554,
843
+ "<|23.82|>": 51555,
844
+ "<|23.84|>": 51556,
845
+ "<|23.86|>": 51557,
846
+ "<|23.88|>": 51558,
847
+ "<|23.90|>": 51559,
848
+ "<|23.92|>": 51560,
849
+ "<|23.94|>": 51561,
850
+ "<|23.96|>": 51562,
851
+ "<|23.98|>": 51563,
852
+ "<|24.00|>": 51564,
853
+ "<|24.02|>": 51565,
854
+ "<|24.04|>": 51566,
855
+ "<|24.06|>": 51567,
856
+ "<|24.08|>": 51568,
857
+ "<|24.10|>": 51569,
858
+ "<|24.12|>": 51570,
859
+ "<|24.14|>": 51571,
860
+ "<|24.16|>": 51572,
861
+ "<|24.18|>": 51573,
862
+ "<|24.20|>": 51574,
863
+ "<|24.22|>": 51575,
864
+ "<|24.24|>": 51576,
865
+ "<|24.26|>": 51577,
866
+ "<|24.28|>": 51578,
867
+ "<|24.30|>": 51579,
868
+ "<|24.32|>": 51580,
869
+ "<|24.34|>": 51581,
870
+ "<|24.36|>": 51582,
871
+ "<|24.38|>": 51583,
872
+ "<|24.40|>": 51584,
873
+ "<|24.42|>": 51585,
874
+ "<|24.44|>": 51586,
875
+ "<|24.46|>": 51587,
876
+ "<|24.48|>": 51588,
877
+ "<|24.50|>": 51589,
878
+ "<|24.52|>": 51590,
879
+ "<|24.54|>": 51591,
880
+ "<|24.56|>": 51592,
881
+ "<|24.58|>": 51593,
882
+ "<|24.60|>": 51594,
883
+ "<|24.62|>": 51595,
884
+ "<|24.64|>": 51596,
885
+ "<|24.66|>": 51597,
886
+ "<|24.68|>": 51598,
887
+ "<|24.70|>": 51599,
888
+ "<|24.72|>": 51600,
889
+ "<|24.74|>": 51601,
890
+ "<|24.76|>": 51602,
891
+ "<|24.78|>": 51603,
892
+ "<|24.80|>": 51604,
893
+ "<|24.82|>": 51605,
894
+ "<|24.84|>": 51606,
895
+ "<|24.86|>": 51607,
896
+ "<|24.88|>": 51608,
897
+ "<|24.90|>": 51609,
898
+ "<|24.92|>": 51610,
899
+ "<|24.94|>": 51611,
900
+ "<|24.96|>": 51612,
901
+ "<|24.98|>": 51613,
902
+ "<|25.00|>": 51614,
903
+ "<|25.02|>": 51615,
904
+ "<|25.04|>": 51616,
905
+ "<|25.06|>": 51617,
906
+ "<|25.08|>": 51618,
907
+ "<|25.10|>": 51619,
908
+ "<|25.12|>": 51620,
909
+ "<|25.14|>": 51621,
910
+ "<|25.16|>": 51622,
911
+ "<|25.18|>": 51623,
912
+ "<|25.20|>": 51624,
913
+ "<|25.22|>": 51625,
914
+ "<|25.24|>": 51626,
915
+ "<|25.26|>": 51627,
916
+ "<|25.28|>": 51628,
917
+ "<|25.30|>": 51629,
918
+ "<|25.32|>": 51630,
919
+ "<|25.34|>": 51631,
920
+ "<|25.36|>": 51632,
921
+ "<|25.38|>": 51633,
922
+ "<|25.40|>": 51634,
923
+ "<|25.42|>": 51635,
924
+ "<|25.44|>": 51636,
925
+ "<|25.46|>": 51637,
926
+ "<|25.48|>": 51638,
927
+ "<|25.50|>": 51639,
928
+ "<|25.52|>": 51640,
929
+ "<|25.54|>": 51641,
930
+ "<|25.56|>": 51642,
931
+ "<|25.58|>": 51643,
932
+ "<|25.60|>": 51644,
933
+ "<|25.62|>": 51645,
934
+ "<|25.64|>": 51646,
935
+ "<|25.66|>": 51647,
936
+ "<|25.68|>": 51648,
937
+ "<|25.70|>": 51649,
938
+ "<|25.72|>": 51650,
939
+ "<|25.74|>": 51651,
940
+ "<|25.76|>": 51652,
941
+ "<|25.78|>": 51653,
942
+ "<|25.80|>": 51654,
943
+ "<|25.82|>": 51655,
944
+ "<|25.84|>": 51656,
945
+ "<|25.86|>": 51657,
946
+ "<|25.88|>": 51658,
947
+ "<|25.90|>": 51659,
948
+ "<|25.92|>": 51660,
949
+ "<|25.94|>": 51661,
950
+ "<|25.96|>": 51662,
951
+ "<|25.98|>": 51663,
952
+ "<|26.00|>": 51664,
953
+ "<|26.02|>": 51665,
954
+ "<|26.04|>": 51666,
955
+ "<|26.06|>": 51667,
956
+ "<|26.08|>": 51668,
957
+ "<|26.10|>": 51669,
958
+ "<|26.12|>": 51670,
959
+ "<|26.14|>": 51671,
960
+ "<|26.16|>": 51672,
961
+ "<|26.18|>": 51673,
962
+ "<|26.20|>": 51674,
963
+ "<|26.22|>": 51675,
964
+ "<|26.24|>": 51676,
965
+ "<|26.26|>": 51677,
966
+ "<|26.28|>": 51678,
967
+ "<|26.30|>": 51679,
968
+ "<|26.32|>": 51680,
969
+ "<|26.34|>": 51681,
970
+ "<|26.36|>": 51682,
971
+ "<|26.38|>": 51683,
972
+ "<|26.40|>": 51684,
973
+ "<|26.42|>": 51685,
974
+ "<|26.44|>": 51686,
975
+ "<|26.46|>": 51687,
976
+ "<|26.48|>": 51688,
977
+ "<|26.50|>": 51689,
978
+ "<|26.52|>": 51690,
979
+ "<|26.54|>": 51691,
980
+ "<|26.56|>": 51692,
981
+ "<|26.58|>": 51693,
982
+ "<|26.60|>": 51694,
983
+ "<|26.62|>": 51695,
984
+ "<|26.64|>": 51696,
985
+ "<|26.66|>": 51697,
986
+ "<|26.68|>": 51698,
987
+ "<|26.70|>": 51699,
988
+ "<|26.72|>": 51700,
989
+ "<|26.74|>": 51701,
990
+ "<|26.76|>": 51702,
991
+ "<|26.78|>": 51703,
992
+ "<|26.80|>": 51704,
993
+ "<|26.82|>": 51705,
994
+ "<|26.84|>": 51706,
995
+ "<|26.86|>": 51707,
996
+ "<|26.88|>": 51708,
997
+ "<|26.90|>": 51709,
998
+ "<|26.92|>": 51710,
999
+ "<|26.94|>": 51711,
1000
+ "<|26.96|>": 51712,
1001
+ "<|26.98|>": 51713,
1002
+ "<|27.00|>": 51714,
1003
+ "<|27.02|>": 51715,
1004
+ "<|27.04|>": 51716,
1005
+ "<|27.06|>": 51717,
1006
+ "<|27.08|>": 51718,
1007
+ "<|27.10|>": 51719,
1008
+ "<|27.12|>": 51720,
1009
+ "<|27.14|>": 51721,
1010
+ "<|27.16|>": 51722,
1011
+ "<|27.18|>": 51723,
1012
+ "<|27.20|>": 51724,
1013
+ "<|27.22|>": 51725,
1014
+ "<|27.24|>": 51726,
1015
+ "<|27.26|>": 51727,
1016
+ "<|27.28|>": 51728,
1017
+ "<|27.30|>": 51729,
1018
+ "<|27.32|>": 51730,
1019
+ "<|27.34|>": 51731,
1020
+ "<|27.36|>": 51732,
1021
+ "<|27.38|>": 51733,
1022
+ "<|27.40|>": 51734,
1023
+ "<|27.42|>": 51735,
1024
+ "<|27.44|>": 51736,
1025
+ "<|27.46|>": 51737,
1026
+ "<|27.48|>": 51738,
1027
+ "<|27.50|>": 51739,
1028
+ "<|27.52|>": 51740,
1029
+ "<|27.54|>": 51741,
1030
+ "<|27.56|>": 51742,
1031
+ "<|27.58|>": 51743,
1032
+ "<|27.60|>": 51744,
1033
+ "<|27.62|>": 51745,
1034
+ "<|27.64|>": 51746,
1035
+ "<|27.66|>": 51747,
1036
+ "<|27.68|>": 51748,
1037
+ "<|27.70|>": 51749,
1038
+ "<|27.72|>": 51750,
1039
+ "<|27.74|>": 51751,
1040
+ "<|27.76|>": 51752,
1041
+ "<|27.78|>": 51753,
1042
+ "<|27.80|>": 51754,
1043
+ "<|27.82|>": 51755,
1044
+ "<|27.84|>": 51756,
1045
+ "<|27.86|>": 51757,
1046
+ "<|27.88|>": 51758,
1047
+ "<|27.90|>": 51759,
1048
+ "<|27.92|>": 51760,
1049
+ "<|27.94|>": 51761,
1050
+ "<|27.96|>": 51762,
1051
+ "<|27.98|>": 51763,
1052
+ "<|28.00|>": 51764,
1053
+ "<|28.02|>": 51765,
1054
+ "<|28.04|>": 51766,
1055
+ "<|28.06|>": 51767,
1056
+ "<|28.08|>": 51768,
1057
+ "<|28.10|>": 51769,
1058
+ "<|28.12|>": 51770,
1059
+ "<|28.14|>": 51771,
1060
+ "<|28.16|>": 51772,
1061
+ "<|28.18|>": 51773,
1062
+ "<|28.20|>": 51774,
1063
+ "<|28.22|>": 51775,
1064
+ "<|28.24|>": 51776,
1065
+ "<|28.26|>": 51777,
1066
+ "<|28.28|>": 51778,
1067
+ "<|28.30|>": 51779,
1068
+ "<|28.32|>": 51780,
1069
+ "<|28.34|>": 51781,
1070
+ "<|28.36|>": 51782,
1071
+ "<|28.38|>": 51783,
1072
+ "<|28.40|>": 51784,
1073
+ "<|28.42|>": 51785,
1074
+ "<|28.44|>": 51786,
1075
+ "<|28.46|>": 51787,
1076
+ "<|28.48|>": 51788,
1077
+ "<|28.50|>": 51789,
1078
+ "<|28.52|>": 51790,
1079
+ "<|28.54|>": 51791,
1080
+ "<|28.56|>": 51792,
1081
+ "<|28.58|>": 51793,
1082
+ "<|28.60|>": 51794,
1083
+ "<|28.62|>": 51795,
1084
+ "<|28.64|>": 51796,
1085
+ "<|28.66|>": 51797,
1086
+ "<|28.68|>": 51798,
1087
+ "<|28.70|>": 51799,
1088
+ "<|28.72|>": 51800,
1089
+ "<|28.74|>": 51801,
1090
+ "<|28.76|>": 51802,
1091
+ "<|28.78|>": 51803,
1092
+ "<|28.80|>": 51804,
1093
+ "<|28.82|>": 51805,
1094
+ "<|28.84|>": 51806,
1095
+ "<|28.86|>": 51807,
1096
+ "<|28.88|>": 51808,
1097
+ "<|28.90|>": 51809,
1098
+ "<|28.92|>": 51810,
1099
+ "<|28.94|>": 51811,
1100
+ "<|28.96|>": 51812,
1101
+ "<|28.98|>": 51813,
1102
+ "<|29.00|>": 51814,
1103
+ "<|29.02|>": 51815,
1104
+ "<|29.04|>": 51816,
1105
+ "<|29.06|>": 51817,
1106
+ "<|29.08|>": 51818,
1107
+ "<|29.10|>": 51819,
1108
+ "<|29.12|>": 51820,
1109
+ "<|29.14|>": 51821,
1110
+ "<|29.16|>": 51822,
1111
+ "<|29.18|>": 51823,
1112
+ "<|29.20|>": 51824,
1113
+ "<|29.22|>": 51825,
1114
+ "<|29.24|>": 51826,
1115
+ "<|29.26|>": 51827,
1116
+ "<|29.28|>": 51828,
1117
+ "<|29.30|>": 51829,
1118
+ "<|29.32|>": 51830,
1119
+ "<|29.34|>": 51831,
1120
+ "<|29.36|>": 51832,
1121
+ "<|29.38|>": 51833,
1122
+ "<|29.40|>": 51834,
1123
+ "<|29.42|>": 51835,
1124
+ "<|29.44|>": 51836,
1125
+ "<|29.46|>": 51837,
1126
+ "<|29.48|>": 51838,
1127
+ "<|29.50|>": 51839,
1128
+ "<|29.52|>": 51840,
1129
+ "<|29.54|>": 51841,
1130
+ "<|29.56|>": 51842,
1131
+ "<|29.58|>": 51843,
1132
+ "<|29.60|>": 51844,
1133
+ "<|29.62|>": 51845,
1134
+ "<|29.64|>": 51846,
1135
+ "<|29.66|>": 51847,
1136
+ "<|29.68|>": 51848,
1137
+ "<|29.70|>": 51849,
1138
+ "<|29.72|>": 51850,
1139
+ "<|29.74|>": 51851,
1140
+ "<|29.76|>": 51852,
1141
+ "<|29.78|>": 51853,
1142
+ "<|29.80|>": 51854,
1143
+ "<|29.82|>": 51855,
1144
+ "<|29.84|>": 51856,
1145
+ "<|29.86|>": 51857,
1146
+ "<|29.88|>": 51858,
1147
+ "<|29.90|>": 51859,
1148
+ "<|29.92|>": 51860,
1149
+ "<|29.94|>": 51861,
1150
+ "<|29.96|>": 51862,
1151
+ "<|29.98|>": 51863,
1152
+ "<|3.00|>": 50514,
1153
+ "<|3.02|>": 50515,
1154
+ "<|3.04|>": 50516,
1155
+ "<|3.06|>": 50517,
1156
+ "<|3.08|>": 50518,
1157
+ "<|3.10|>": 50519,
1158
+ "<|3.12|>": 50520,
1159
+ "<|3.14|>": 50521,
1160
+ "<|3.16|>": 50522,
1161
+ "<|3.18|>": 50523,
1162
+ "<|3.20|>": 50524,
1163
+ "<|3.22|>": 50525,
1164
+ "<|3.24|>": 50526,
1165
+ "<|3.26|>": 50527,
1166
+ "<|3.28|>": 50528,
1167
+ "<|3.30|>": 50529,
1168
+ "<|3.32|>": 50530,
1169
+ "<|3.34|>": 50531,
1170
+ "<|3.36|>": 50532,
1171
+ "<|3.38|>": 50533,
1172
+ "<|3.40|>": 50534,
1173
+ "<|3.42|>": 50535,
1174
+ "<|3.44|>": 50536,
1175
+ "<|3.46|>": 50537,
1176
+ "<|3.48|>": 50538,
1177
+ "<|3.50|>": 50539,
1178
+ "<|3.52|>": 50540,
1179
+ "<|3.54|>": 50541,
1180
+ "<|3.56|>": 50542,
1181
+ "<|3.58|>": 50543,
1182
+ "<|3.60|>": 50544,
1183
+ "<|3.62|>": 50545,
1184
+ "<|3.64|>": 50546,
1185
+ "<|3.66|>": 50547,
1186
+ "<|3.68|>": 50548,
1187
+ "<|3.70|>": 50549,
1188
+ "<|3.72|>": 50550,
1189
+ "<|3.74|>": 50551,
1190
+ "<|3.76|>": 50552,
1191
+ "<|3.78|>": 50553,
1192
+ "<|3.80|>": 50554,
1193
+ "<|3.82|>": 50555,
1194
+ "<|3.84|>": 50556,
1195
+ "<|3.86|>": 50557,
1196
+ "<|3.88|>": 50558,
1197
+ "<|3.90|>": 50559,
1198
+ "<|3.92|>": 50560,
1199
+ "<|3.94|>": 50561,
1200
+ "<|3.96|>": 50562,
1201
+ "<|3.98|>": 50563,
1202
+ "<|30.00|>": 51864,
1203
+ "<|4.00|>": 50564,
1204
+ "<|4.02|>": 50565,
1205
+ "<|4.04|>": 50566,
1206
+ "<|4.06|>": 50567,
1207
+ "<|4.08|>": 50568,
1208
+ "<|4.10|>": 50569,
1209
+ "<|4.12|>": 50570,
1210
+ "<|4.14|>": 50571,
1211
+ "<|4.16|>": 50572,
1212
+ "<|4.18|>": 50573,
1213
+ "<|4.20|>": 50574,
1214
+ "<|4.22|>": 50575,
1215
+ "<|4.24|>": 50576,
1216
+ "<|4.26|>": 50577,
1217
+ "<|4.28|>": 50578,
1218
+ "<|4.30|>": 50579,
1219
+ "<|4.32|>": 50580,
1220
+ "<|4.34|>": 50581,
1221
+ "<|4.36|>": 50582,
1222
+ "<|4.38|>": 50583,
1223
+ "<|4.40|>": 50584,
1224
+ "<|4.42|>": 50585,
1225
+ "<|4.44|>": 50586,
1226
+ "<|4.46|>": 50587,
1227
+ "<|4.48|>": 50588,
1228
+ "<|4.50|>": 50589,
1229
+ "<|4.52|>": 50590,
1230
+ "<|4.54|>": 50591,
1231
+ "<|4.56|>": 50592,
1232
+ "<|4.58|>": 50593,
1233
+ "<|4.60|>": 50594,
1234
+ "<|4.62|>": 50595,
1235
+ "<|4.64|>": 50596,
1236
+ "<|4.66|>": 50597,
1237
+ "<|4.68|>": 50598,
1238
+ "<|4.70|>": 50599,
1239
+ "<|4.72|>": 50600,
1240
+ "<|4.74|>": 50601,
1241
+ "<|4.76|>": 50602,
1242
+ "<|4.78|>": 50603,
1243
+ "<|4.80|>": 50604,
1244
+ "<|4.82|>": 50605,
1245
+ "<|4.84|>": 50606,
1246
+ "<|4.86|>": 50607,
1247
+ "<|4.88|>": 50608,
1248
+ "<|4.90|>": 50609,
1249
+ "<|4.92|>": 50610,
1250
+ "<|4.94|>": 50611,
1251
+ "<|4.96|>": 50612,
1252
+ "<|4.98|>": 50613,
1253
+ "<|5.00|>": 50614,
1254
+ "<|5.02|>": 50615,
1255
+ "<|5.04|>": 50616,
1256
+ "<|5.06|>": 50617,
1257
+ "<|5.08|>": 50618,
1258
+ "<|5.10|>": 50619,
1259
+ "<|5.12|>": 50620,
1260
+ "<|5.14|>": 50621,
1261
+ "<|5.16|>": 50622,
1262
+ "<|5.18|>": 50623,
1263
+ "<|5.20|>": 50624,
1264
+ "<|5.22|>": 50625,
1265
+ "<|5.24|>": 50626,
1266
+ "<|5.26|>": 50627,
1267
+ "<|5.28|>": 50628,
1268
+ "<|5.30|>": 50629,
1269
+ "<|5.32|>": 50630,
1270
+ "<|5.34|>": 50631,
1271
+ "<|5.36|>": 50632,
1272
+ "<|5.38|>": 50633,
1273
+ "<|5.40|>": 50634,
1274
+ "<|5.42|>": 50635,
1275
+ "<|5.44|>": 50636,
1276
+ "<|5.46|>": 50637,
1277
+ "<|5.48|>": 50638,
1278
+ "<|5.50|>": 50639,
1279
+ "<|5.52|>": 50640,
1280
+ "<|5.54|>": 50641,
1281
+ "<|5.56|>": 50642,
1282
+ "<|5.58|>": 50643,
1283
+ "<|5.60|>": 50644,
1284
+ "<|5.62|>": 50645,
1285
+ "<|5.64|>": 50646,
1286
+ "<|5.66|>": 50647,
1287
+ "<|5.68|>": 50648,
1288
+ "<|5.70|>": 50649,
1289
+ "<|5.72|>": 50650,
1290
+ "<|5.74|>": 50651,
1291
+ "<|5.76|>": 50652,
1292
+ "<|5.78|>": 50653,
1293
+ "<|5.80|>": 50654,
1294
+ "<|5.82|>": 50655,
1295
+ "<|5.84|>": 50656,
1296
+ "<|5.86|>": 50657,
1297
+ "<|5.88|>": 50658,
1298
+ "<|5.90|>": 50659,
1299
+ "<|5.92|>": 50660,
1300
+ "<|5.94|>": 50661,
1301
+ "<|5.96|>": 50662,
1302
+ "<|5.98|>": 50663,
1303
+ "<|6.00|>": 50664,
1304
+ "<|6.02|>": 50665,
1305
+ "<|6.04|>": 50666,
1306
+ "<|6.06|>": 50667,
1307
+ "<|6.08|>": 50668,
1308
+ "<|6.10|>": 50669,
1309
+ "<|6.12|>": 50670,
1310
+ "<|6.14|>": 50671,
1311
+ "<|6.16|>": 50672,
1312
+ "<|6.18|>": 50673,
1313
+ "<|6.20|>": 50674,
1314
+ "<|6.22|>": 50675,
1315
+ "<|6.24|>": 50676,
1316
+ "<|6.26|>": 50677,
1317
+ "<|6.28|>": 50678,
1318
+ "<|6.30|>": 50679,
1319
+ "<|6.32|>": 50680,
1320
+ "<|6.34|>": 50681,
1321
+ "<|6.36|>": 50682,
1322
+ "<|6.38|>": 50683,
1323
+ "<|6.40|>": 50684,
1324
+ "<|6.42|>": 50685,
1325
+ "<|6.44|>": 50686,
1326
+ "<|6.46|>": 50687,
1327
+ "<|6.48|>": 50688,
1328
+ "<|6.50|>": 50689,
1329
+ "<|6.52|>": 50690,
1330
+ "<|6.54|>": 50691,
1331
+ "<|6.56|>": 50692,
1332
+ "<|6.58|>": 50693,
1333
+ "<|6.60|>": 50694,
1334
+ "<|6.62|>": 50695,
1335
+ "<|6.64|>": 50696,
1336
+ "<|6.66|>": 50697,
1337
+ "<|6.68|>": 50698,
1338
+ "<|6.70|>": 50699,
1339
+ "<|6.72|>": 50700,
1340
+ "<|6.74|>": 50701,
1341
+ "<|6.76|>": 50702,
1342
+ "<|6.78|>": 50703,
1343
+ "<|6.80|>": 50704,
1344
+ "<|6.82|>": 50705,
1345
+ "<|6.84|>": 50706,
1346
+ "<|6.86|>": 50707,
1347
+ "<|6.88|>": 50708,
1348
+ "<|6.90|>": 50709,
1349
+ "<|6.92|>": 50710,
1350
+ "<|6.94|>": 50711,
1351
+ "<|6.96|>": 50712,
1352
+ "<|6.98|>": 50713,
1353
+ "<|7.00|>": 50714,
1354
+ "<|7.02|>": 50715,
1355
+ "<|7.04|>": 50716,
1356
+ "<|7.06|>": 50717,
1357
+ "<|7.08|>": 50718,
1358
+ "<|7.10|>": 50719,
1359
+ "<|7.12|>": 50720,
1360
+ "<|7.14|>": 50721,
1361
+ "<|7.16|>": 50722,
1362
+ "<|7.18|>": 50723,
1363
+ "<|7.20|>": 50724,
1364
+ "<|7.22|>": 50725,
1365
+ "<|7.24|>": 50726,
1366
+ "<|7.26|>": 50727,
1367
+ "<|7.28|>": 50728,
1368
+ "<|7.30|>": 50729,
1369
+ "<|7.32|>": 50730,
1370
+ "<|7.34|>": 50731,
1371
+ "<|7.36|>": 50732,
1372
+ "<|7.38|>": 50733,
1373
+ "<|7.40|>": 50734,
1374
+ "<|7.42|>": 50735,
1375
+ "<|7.44|>": 50736,
1376
+ "<|7.46|>": 50737,
1377
+ "<|7.48|>": 50738,
1378
+ "<|7.50|>": 50739,
1379
+ "<|7.52|>": 50740,
1380
+ "<|7.54|>": 50741,
1381
+ "<|7.56|>": 50742,
1382
+ "<|7.58|>": 50743,
1383
+ "<|7.60|>": 50744,
1384
+ "<|7.62|>": 50745,
1385
+ "<|7.64|>": 50746,
1386
+ "<|7.66|>": 50747,
1387
+ "<|7.68|>": 50748,
1388
+ "<|7.70|>": 50749,
1389
+ "<|7.72|>": 50750,
1390
+ "<|7.74|>": 50751,
1391
+ "<|7.76|>": 50752,
1392
+ "<|7.78|>": 50753,
1393
+ "<|7.80|>": 50754,
1394
+ "<|7.82|>": 50755,
1395
+ "<|7.84|>": 50756,
1396
+ "<|7.86|>": 50757,
1397
+ "<|7.88|>": 50758,
1398
+ "<|7.90|>": 50759,
1399
+ "<|7.92|>": 50760,
1400
+ "<|7.94|>": 50761,
1401
+ "<|7.96|>": 50762,
1402
+ "<|7.98|>": 50763,
1403
+ "<|8.00|>": 50764,
1404
+ "<|8.02|>": 50765,
1405
+ "<|8.04|>": 50766,
1406
+ "<|8.06|>": 50767,
1407
+ "<|8.08|>": 50768,
1408
+ "<|8.10|>": 50769,
1409
+ "<|8.12|>": 50770,
1410
+ "<|8.14|>": 50771,
1411
+ "<|8.16|>": 50772,
1412
+ "<|8.18|>": 50773,
1413
+ "<|8.20|>": 50774,
1414
+ "<|8.22|>": 50775,
1415
+ "<|8.24|>": 50776,
1416
+ "<|8.26|>": 50777,
1417
+ "<|8.28|>": 50778,
1418
+ "<|8.30|>": 50779,
1419
+ "<|8.32|>": 50780,
1420
+ "<|8.34|>": 50781,
1421
+ "<|8.36|>": 50782,
1422
+ "<|8.38|>": 50783,
1423
+ "<|8.40|>": 50784,
1424
+ "<|8.42|>": 50785,
1425
+ "<|8.44|>": 50786,
1426
+ "<|8.46|>": 50787,
1427
+ "<|8.48|>": 50788,
1428
+ "<|8.50|>": 50789,
1429
+ "<|8.52|>": 50790,
1430
+ "<|8.54|>": 50791,
1431
+ "<|8.56|>": 50792,
1432
+ "<|8.58|>": 50793,
1433
+ "<|8.60|>": 50794,
1434
+ "<|8.62|>": 50795,
1435
+ "<|8.64|>": 50796,
1436
+ "<|8.66|>": 50797,
1437
+ "<|8.68|>": 50798,
1438
+ "<|8.70|>": 50799,
1439
+ "<|8.72|>": 50800,
1440
+ "<|8.74|>": 50801,
1441
+ "<|8.76|>": 50802,
1442
+ "<|8.78|>": 50803,
1443
+ "<|8.80|>": 50804,
1444
+ "<|8.82|>": 50805,
1445
+ "<|8.84|>": 50806,
1446
+ "<|8.86|>": 50807,
1447
+ "<|8.88|>": 50808,
1448
+ "<|8.90|>": 50809,
1449
+ "<|8.92|>": 50810,
1450
+ "<|8.94|>": 50811,
1451
+ "<|8.96|>": 50812,
1452
+ "<|8.98|>": 50813,
1453
+ "<|9.00|>": 50814,
1454
+ "<|9.02|>": 50815,
1455
+ "<|9.04|>": 50816,
1456
+ "<|9.06|>": 50817,
1457
+ "<|9.08|>": 50818,
1458
+ "<|9.10|>": 50819,
1459
+ "<|9.12|>": 50820,
1460
+ "<|9.14|>": 50821,
1461
+ "<|9.16|>": 50822,
1462
+ "<|9.18|>": 50823,
1463
+ "<|9.20|>": 50824,
1464
+ "<|9.22|>": 50825,
1465
+ "<|9.24|>": 50826,
1466
+ "<|9.26|>": 50827,
1467
+ "<|9.28|>": 50828,
1468
+ "<|9.30|>": 50829,
1469
+ "<|9.32|>": 50830,
1470
+ "<|9.34|>": 50831,
1471
+ "<|9.36|>": 50832,
1472
+ "<|9.38|>": 50833,
1473
+ "<|9.40|>": 50834,
1474
+ "<|9.42|>": 50835,
1475
+ "<|9.44|>": 50836,
1476
+ "<|9.46|>": 50837,
1477
+ "<|9.48|>": 50838,
1478
+ "<|9.50|>": 50839,
1479
+ "<|9.52|>": 50840,
1480
+ "<|9.54|>": 50841,
1481
+ "<|9.56|>": 50842,
1482
+ "<|9.58|>": 50843,
1483
+ "<|9.60|>": 50844,
1484
+ "<|9.62|>": 50845,
1485
+ "<|9.64|>": 50846,
1486
+ "<|9.66|>": 50847,
1487
+ "<|9.68|>": 50848,
1488
+ "<|9.70|>": 50849,
1489
+ "<|9.72|>": 50850,
1490
+ "<|9.74|>": 50851,
1491
+ "<|9.76|>": 50852,
1492
+ "<|9.78|>": 50853,
1493
+ "<|9.80|>": 50854,
1494
+ "<|9.82|>": 50855,
1495
+ "<|9.84|>": 50856,
1496
+ "<|9.86|>": 50857,
1497
+ "<|9.88|>": 50858,
1498
+ "<|9.90|>": 50859,
1499
+ "<|9.92|>": 50860,
1500
+ "<|9.94|>": 50861,
1501
+ "<|9.96|>": 50862,
1502
+ "<|9.98|>": 50863,
1503
+ "<|af|>": 50327,
1504
+ "<|am|>": 50334,
1505
+ "<|ar|>": 50272,
1506
+ "<|as|>": 50350,
1507
+ "<|az|>": 50304,
1508
+ "<|ba|>": 50355,
1509
+ "<|be|>": 50330,
1510
+ "<|bg|>": 50292,
1511
+ "<|bn|>": 50302,
1512
+ "<|bo|>": 50347,
1513
+ "<|br|>": 50309,
1514
+ "<|bs|>": 50315,
1515
+ "<|ca|>": 50270,
1516
+ "<|cs|>": 50283,
1517
+ "<|cy|>": 50297,
1518
+ "<|da|>": 50285,
1519
+ "<|de|>": 50261,
1520
+ "<|el|>": 50281,
1521
+ "<|en|>": 50259,
1522
+ "<|es|>": 50262,
1523
+ "<|et|>": 50307,
1524
+ "<|eu|>": 50310,
1525
+ "<|fa|>": 50300,
1526
+ "<|fi|>": 50277,
1527
+ "<|fo|>": 50338,
1528
+ "<|fr|>": 50265,
1529
+ "<|gl|>": 50319,
1530
+ "<|gu|>": 50333,
1531
+ "<|haw|>": 50352,
1532
+ "<|ha|>": 50354,
1533
+ "<|he|>": 50279,
1534
+ "<|hi|>": 50276,
1535
+ "<|hr|>": 50291,
1536
+ "<|ht|>": 50339,
1537
+ "<|hu|>": 50286,
1538
+ "<|hy|>": 50312,
1539
+ "<|id|>": 50275,
1540
+ "<|is|>": 50311,
1541
+ "<|it|>": 50274,
1542
+ "<|ja|>": 50266,
1543
+ "<|jw|>": 50356,
1544
+ "<|ka|>": 50329,
1545
+ "<|kk|>": 50316,
1546
+ "<|km|>": 50323,
1547
+ "<|kn|>": 50306,
1548
+ "<|ko|>": 50264,
1549
+ "<|la|>": 50294,
1550
+ "<|lb|>": 50345,
1551
+ "<|ln|>": 50353,
1552
+ "<|lo|>": 50336,
1553
+ "<|lt|>": 50293,
1554
+ "<|lv|>": 50301,
1555
+ "<|mg|>": 50349,
1556
+ "<|mi|>": 50295,
1557
+ "<|mk|>": 50308,
1558
+ "<|ml|>": 50296,
1559
+ "<|mn|>": 50314,
1560
+ "<|mr|>": 50320,
1561
+ "<|ms|>": 50282,
1562
+ "<|mt|>": 50343,
1563
+ "<|my|>": 50346,
1564
+ "<|ne|>": 50313,
1565
+ "<|nl|>": 50271,
1566
+ "<|nn|>": 50342,
1567
+ "<|nocaptions|>": 50362,
1568
+ "<|notimestamps|>": 50363,
1569
+ "<|no|>": 50288,
1570
+ "<|oc|>": 50328,
1571
+ "<|pa|>": 50321,
1572
+ "<|pl|>": 50269,
1573
+ "<|ps|>": 50340,
1574
+ "<|pt|>": 50267,
1575
+ "<|ro|>": 50284,
1576
+ "<|ru|>": 50263,
1577
+ "<|sa|>": 50344,
1578
+ "<|sd|>": 50332,
1579
+ "<|si|>": 50322,
1580
+ "<|sk|>": 50298,
1581
+ "<|sl|>": 50305,
1582
+ "<|sn|>": 50324,
1583
+ "<|so|>": 50326,
1584
+ "<|sq|>": 50317,
1585
+ "<|sr|>": 50303,
1586
+ "<|startoflm|>": 50360,
1587
+ "<|startofprev|>": 50361,
1588
+ "<|startoftranscript|>": 50258,
1589
+ "<|su|>": 50357,
1590
+ "<|sv|>": 50273,
1591
+ "<|sw|>": 50318,
1592
+ "<|ta|>": 50287,
1593
+ "<|te|>": 50299,
1594
+ "<|tg|>": 50331,
1595
+ "<|th|>": 50289,
1596
+ "<|tk|>": 50341,
1597
+ "<|tl|>": 50348,
1598
+ "<|transcribe|>": 50359,
1599
+ "<|translate|>": 50358,
1600
+ "<|tr|>": 50268,
1601
+ "<|tt|>": 50351,
1602
+ "<|uk|>": 50280,
1603
+ "<|ur|>": 50290,
1604
+ "<|uz|>": 50337,
1605
+ "<|vi|>": 50278,
1606
+ "<|yi|>": 50335,
1607
+ "<|yo|>": 50325,
1608
+ "<|zh|>": 50260
1609
+ }
onnx/config.json ADDED
@@ -0,0 +1,154 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "./config.json",
3
+ "activation_dropout": 0.1,
4
+ "activation_function": "gelu",
5
+ "apply_spec_augment": false,
6
+ "architectures": [
7
+ "WhisperForConditionalGeneration"
8
+ ],
9
+ "attention_dropout": 0.0,
10
+ "begin_suppress_tokens": [
11
+ 220,
12
+ 50257
13
+ ],
14
+ "bos_token_id": 50257,
15
+ "classifier_proj_size": 256,
16
+ "d_model": 384,
17
+ "decoder_attention_heads": 6,
18
+ "decoder_ffn_dim": 1536,
19
+ "decoder_layerdrop": 0.0,
20
+ "decoder_layers": 4,
21
+ "decoder_start_token_id": 50258,
22
+ "dropout": 0.0,
23
+ "encoder_attention_heads": 6,
24
+ "encoder_ffn_dim": 1536,
25
+ "encoder_layerdrop": 0.0,
26
+ "encoder_layers": 4,
27
+ "eos_token_id": 50257,
28
+ "forced_decoder_ids": [
29
+ [
30
+ 1,
31
+ 50259
32
+ ],
33
+ [
34
+ 2,
35
+ 50359
36
+ ],
37
+ [
38
+ 3,
39
+ 50363
40
+ ]
41
+ ],
42
+ "init_std": 0.02,
43
+ "is_encoder_decoder": true,
44
+ "mask_feature_length": 10,
45
+ "mask_feature_min_masks": 0,
46
+ "mask_feature_prob": 0.0,
47
+ "mask_time_length": 10,
48
+ "mask_time_min_masks": 2,
49
+ "mask_time_prob": 0.05,
50
+ "max_length": 448,
51
+ "max_source_positions": 1500,
52
+ "max_target_positions": 448,
53
+ "median_filter_width": 7,
54
+ "model_type": "whisper",
55
+ "num_hidden_layers": 4,
56
+ "num_mel_bins": 80,
57
+ "pad_token_id": 50257,
58
+ "scale_embedding": false,
59
+ "suppress_tokens": [
60
+ 1,
61
+ 2,
62
+ 7,
63
+ 8,
64
+ 9,
65
+ 10,
66
+ 14,
67
+ 25,
68
+ 26,
69
+ 27,
70
+ 28,
71
+ 29,
72
+ 31,
73
+ 58,
74
+ 59,
75
+ 60,
76
+ 61,
77
+ 62,
78
+ 63,
79
+ 90,
80
+ 91,
81
+ 92,
82
+ 93,
83
+ 359,
84
+ 503,
85
+ 522,
86
+ 542,
87
+ 873,
88
+ 893,
89
+ 902,
90
+ 918,
91
+ 922,
92
+ 931,
93
+ 1350,
94
+ 1853,
95
+ 1982,
96
+ 2460,
97
+ 2627,
98
+ 3246,
99
+ 3253,
100
+ 3268,
101
+ 3536,
102
+ 3846,
103
+ 3961,
104
+ 4183,
105
+ 4667,
106
+ 6585,
107
+ 6647,
108
+ 7273,
109
+ 9061,
110
+ 9383,
111
+ 10428,
112
+ 10929,
113
+ 11938,
114
+ 12033,
115
+ 12331,
116
+ 12562,
117
+ 13793,
118
+ 14157,
119
+ 14635,
120
+ 15265,
121
+ 15618,
122
+ 16553,
123
+ 16604,
124
+ 18362,
125
+ 18956,
126
+ 20075,
127
+ 21675,
128
+ 22520,
129
+ 26130,
130
+ 26161,
131
+ 26435,
132
+ 28279,
133
+ 29464,
134
+ 31650,
135
+ 32302,
136
+ 32470,
137
+ 36865,
138
+ 42863,
139
+ 47425,
140
+ 49870,
141
+ 50254,
142
+ 50258,
143
+ 50358,
144
+ 50359,
145
+ 50360,
146
+ 50361,
147
+ 50362
148
+ ],
149
+ "torch_dtype": "float32",
150
+ "transformers_version": "4.34.1",
151
+ "use_cache": true,
152
+ "use_weighted_layer_sum": false,
153
+ "vocab_size": 51865
154
+ }
onnx/decoder_model.onnx ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a4cfa372d7286de10f6959c1fbd417d976f8c640b2f02112f549fe179b40fae3
3
+ size 198049530
onnx/decoder_with_past_model.onnx ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b2ec4d3614caf98e52b18b3bb99565b5e6ab0287951070b819f6b5672e377206
3
+ size 193295315
onnx/encoder_model.onnx ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:59297900c04d85c8ec347f4080e717ca681019d40aaa515c8fa748d3f078ae1e
3
+ size 32900723
onnx/generation_config.json ADDED
@@ -0,0 +1,253 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alignment_heads": [
3
+ [
4
+ 2,
5
+ 2
6
+ ],
7
+ [
8
+ 3,
9
+ 0
10
+ ],
11
+ [
12
+ 3,
13
+ 2
14
+ ],
15
+ [
16
+ 3,
17
+ 3
18
+ ],
19
+ [
20
+ 3,
21
+ 4
22
+ ],
23
+ [
24
+ 3,
25
+ 5
26
+ ]
27
+ ],
28
+ "begin_suppress_tokens": [
29
+ 220,
30
+ 50257
31
+ ],
32
+ "bos_token_id": 50257,
33
+ "decoder_start_token_id": 50258,
34
+ "eos_token_id": 50257,
35
+ "forced_decoder_ids": [
36
+ [
37
+ 1,
38
+ 50288
39
+ ],
40
+ [
41
+ 2,
42
+ 50359
43
+ ],
44
+ [
45
+ 3,
46
+ 50363
47
+ ]
48
+ ],
49
+ "is_multilingual": true,
50
+ "lang_to_id": {
51
+ "<|af|>": 50327,
52
+ "<|am|>": 50334,
53
+ "<|ar|>": 50272,
54
+ "<|as|>": 50350,
55
+ "<|az|>": 50304,
56
+ "<|ba|>": 50355,
57
+ "<|be|>": 50330,
58
+ "<|bg|>": 50292,
59
+ "<|bn|>": 50302,
60
+ "<|bo|>": 50347,
61
+ "<|br|>": 50309,
62
+ "<|bs|>": 50315,
63
+ "<|ca|>": 50270,
64
+ "<|cs|>": 50283,
65
+ "<|cy|>": 50297,
66
+ "<|da|>": 50285,
67
+ "<|de|>": 50261,
68
+ "<|el|>": 50281,
69
+ "<|en|>": 50259,
70
+ "<|es|>": 50262,
71
+ "<|et|>": 50307,
72
+ "<|eu|>": 50310,
73
+ "<|fa|>": 50300,
74
+ "<|fi|>": 50277,
75
+ "<|fo|>": 50338,
76
+ "<|fr|>": 50265,
77
+ "<|gl|>": 50319,
78
+ "<|gu|>": 50333,
79
+ "<|haw|>": 50352,
80
+ "<|ha|>": 50354,
81
+ "<|he|>": 50279,
82
+ "<|hi|>": 50276,
83
+ "<|hr|>": 50291,
84
+ "<|ht|>": 50339,
85
+ "<|hu|>": 50286,
86
+ "<|hy|>": 50312,
87
+ "<|id|>": 50275,
88
+ "<|is|>": 50311,
89
+ "<|it|>": 50274,
90
+ "<|ja|>": 50266,
91
+ "<|jw|>": 50356,
92
+ "<|ka|>": 50329,
93
+ "<|kk|>": 50316,
94
+ "<|km|>": 50323,
95
+ "<|kn|>": 50306,
96
+ "<|ko|>": 50264,
97
+ "<|la|>": 50294,
98
+ "<|lb|>": 50345,
99
+ "<|ln|>": 50353,
100
+ "<|lo|>": 50336,
101
+ "<|lt|>": 50293,
102
+ "<|lv|>": 50301,
103
+ "<|mg|>": 50349,
104
+ "<|mi|>": 50295,
105
+ "<|mk|>": 50308,
106
+ "<|ml|>": 50296,
107
+ "<|mn|>": 50314,
108
+ "<|mr|>": 50320,
109
+ "<|ms|>": 50282,
110
+ "<|mt|>": 50343,
111
+ "<|my|>": 50346,
112
+ "<|ne|>": 50313,
113
+ "<|nl|>": 50271,
114
+ "<|nn|>": 50342,
115
+ "<|no|>": 50288,
116
+ "<|oc|>": 50328,
117
+ "<|pa|>": 50321,
118
+ "<|pl|>": 50269,
119
+ "<|ps|>": 50340,
120
+ "<|pt|>": 50267,
121
+ "<|ro|>": 50284,
122
+ "<|ru|>": 50263,
123
+ "<|sa|>": 50344,
124
+ "<|sd|>": 50332,
125
+ "<|si|>": 50322,
126
+ "<|sk|>": 50298,
127
+ "<|sl|>": 50305,
128
+ "<|sn|>": 50324,
129
+ "<|so|>": 50326,
130
+ "<|sq|>": 50317,
131
+ "<|sr|>": 50303,
132
+ "<|su|>": 50357,
133
+ "<|sv|>": 50273,
134
+ "<|sw|>": 50318,
135
+ "<|ta|>": 50287,
136
+ "<|te|>": 50299,
137
+ "<|tg|>": 50331,
138
+ "<|th|>": 50289,
139
+ "<|tk|>": 50341,
140
+ "<|tl|>": 50348,
141
+ "<|tr|>": 50268,
142
+ "<|tt|>": 50351,
143
+ "<|uk|>": 50280,
144
+ "<|ur|>": 50290,
145
+ "<|uz|>": 50337,
146
+ "<|vi|>": 50278,
147
+ "<|yi|>": 50335,
148
+ "<|yo|>": 50325,
149
+ "<|zh|>": 50260
150
+ },
151
+ "language": "<|no|>",
152
+ "max_initial_timestamp_index": 1,
153
+ "max_length": 448,
154
+ "no_timestamps_token_id": 50363,
155
+ "pad_token_id": 50257,
156
+ "return_timestamps": false,
157
+ "suppress_tokens": [
158
+ 1,
159
+ 2,
160
+ 7,
161
+ 8,
162
+ 9,
163
+ 10,
164
+ 14,
165
+ 25,
166
+ 26,
167
+ 27,
168
+ 28,
169
+ 29,
170
+ 31,
171
+ 58,
172
+ 59,
173
+ 60,
174
+ 61,
175
+ 62,
176
+ 63,
177
+ 90,
178
+ 91,
179
+ 92,
180
+ 93,
181
+ 359,
182
+ 503,
183
+ 522,
184
+ 542,
185
+ 873,
186
+ 893,
187
+ 902,
188
+ 918,
189
+ 922,
190
+ 931,
191
+ 1350,
192
+ 1853,
193
+ 1982,
194
+ 2460,
195
+ 2627,
196
+ 3246,
197
+ 3253,
198
+ 3268,
199
+ 3536,
200
+ 3846,
201
+ 3961,
202
+ 4183,
203
+ 4667,
204
+ 6585,
205
+ 6647,
206
+ 7273,
207
+ 9061,
208
+ 9383,
209
+ 10428,
210
+ 10929,
211
+ 11938,
212
+ 12033,
213
+ 12331,
214
+ 12562,
215
+ 13793,
216
+ 14157,
217
+ 14635,
218
+ 15265,
219
+ 15618,
220
+ 16553,
221
+ 16604,
222
+ 18362,
223
+ 18956,
224
+ 20075,
225
+ 21675,
226
+ 22520,
227
+ 26130,
228
+ 26161,
229
+ 26435,
230
+ 28279,
231
+ 29464,
232
+ 31650,
233
+ 32302,
234
+ 32470,
235
+ 36865,
236
+ 42863,
237
+ 47425,
238
+ 49870,
239
+ 50254,
240
+ 50258,
241
+ 50358,
242
+ 50359,
243
+ 50360,
244
+ 50361,
245
+ 50362
246
+ ],
247
+ "task": "transcribe",
248
+ "task_to_id": {
249
+ "transcribe": 50359,
250
+ "translate": 50358
251
+ },
252
+ "transformers_version": "4.34.1"
253
+ }
onnx/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
onnx/normalizer.json ADDED
@@ -0,0 +1,1742 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "accessorise": "accessorize",
3
+ "accessorised": "accessorized",
4
+ "accessorises": "accessorizes",
5
+ "accessorising": "accessorizing",
6
+ "acclimatisation": "acclimatization",
7
+ "acclimatise": "acclimatize",
8
+ "acclimatised": "acclimatized",
9
+ "acclimatises": "acclimatizes",
10
+ "acclimatising": "acclimatizing",
11
+ "accoutrements": "accouterments",
12
+ "aeon": "eon",
13
+ "aeons": "eons",
14
+ "aerogramme": "aerogram",
15
+ "aerogrammes": "aerograms",
16
+ "aeroplane": "airplane",
17
+ "aeroplanes": "airplanes",
18
+ "aesthete": "esthete",
19
+ "aesthetes": "esthetes",
20
+ "aesthetic": "esthetic",
21
+ "aesthetically": "esthetically",
22
+ "aesthetics": "esthetics",
23
+ "aetiology": "etiology",
24
+ "ageing": "aging",
25
+ "aggrandisement": "aggrandizement",
26
+ "agonise": "agonize",
27
+ "agonised": "agonized",
28
+ "agonises": "agonizes",
29
+ "agonising": "agonizing",
30
+ "agonisingly": "agonizingly",
31
+ "almanack": "almanac",
32
+ "almanacks": "almanacs",
33
+ "aluminium": "aluminum",
34
+ "amortisable": "amortizable",
35
+ "amortisation": "amortization",
36
+ "amortisations": "amortizations",
37
+ "amortise": "amortize",
38
+ "amortised": "amortized",
39
+ "amortises": "amortizes",
40
+ "amortising": "amortizing",
41
+ "amphitheatre": "amphitheater",
42
+ "amphitheatres": "amphitheaters",
43
+ "anaemia": "anemia",
44
+ "anaemic": "anemic",
45
+ "anaesthesia": "anesthesia",
46
+ "anaesthetic": "anesthetic",
47
+ "anaesthetics": "anesthetics",
48
+ "anaesthetise": "anesthetize",
49
+ "anaesthetised": "anesthetized",
50
+ "anaesthetises": "anesthetizes",
51
+ "anaesthetising": "anesthetizing",
52
+ "anaesthetist": "anesthetist",
53
+ "anaesthetists": "anesthetists",
54
+ "anaesthetize": "anesthetize",
55
+ "anaesthetized": "anesthetized",
56
+ "anaesthetizes": "anesthetizes",
57
+ "anaesthetizing": "anesthetizing",
58
+ "analogue": "analog",
59
+ "analogues": "analogs",
60
+ "analyse": "analyze",
61
+ "analysed": "analyzed",
62
+ "analyses": "analyzes",
63
+ "analysing": "analyzing",
64
+ "anglicise": "anglicize",
65
+ "anglicised": "anglicized",
66
+ "anglicises": "anglicizes",
67
+ "anglicising": "anglicizing",
68
+ "annualised": "annualized",
69
+ "antagonise": "antagonize",
70
+ "antagonised": "antagonized",
71
+ "antagonises": "antagonizes",
72
+ "antagonising": "antagonizing",
73
+ "apologise": "apologize",
74
+ "apologised": "apologized",
75
+ "apologises": "apologizes",
76
+ "apologising": "apologizing",
77
+ "appal": "appall",
78
+ "appals": "appalls",
79
+ "appetiser": "appetizer",
80
+ "appetisers": "appetizers",
81
+ "appetising": "appetizing",
82
+ "appetisingly": "appetizingly",
83
+ "arbour": "arbor",
84
+ "arbours": "arbors",
85
+ "archaeologically": "archeologically",
86
+ "archaeologist": "archeologist",
87
+ "archaeologists": "archeologists",
88
+ "archaeology": "archeology</span>",
89
+ "archeological": "archaeological",
90
+ "ardour": "ardor",
91
+ "armour": "armor",
92
+ "armoured": "armored",
93
+ "armourer": "armorer",
94
+ "armourers": "armorers",
95
+ "armouries": "armories",
96
+ "armoury": "armory",
97
+ "artefact": "artifact",
98
+ "artefacts": "artifacts",
99
+ "authorise": "authorize",
100
+ "authorised": "authorized",
101
+ "authorises": "authorizes",
102
+ "authorising": "authorizing",
103
+ "axe": "ax",
104
+ "backpedalled": "backpedaled",
105
+ "backpedalling": "backpedaling",
106
+ "bannister": "banister",
107
+ "bannisters": "banisters",
108
+ "baptise": "baptize",
109
+ "baptised": "baptized",
110
+ "baptises": "baptizes",
111
+ "baptising": "baptizing",
112
+ "bastardise": "bastardize",
113
+ "bastardised": "bastardized",
114
+ "bastardises": "bastardizes",
115
+ "bastardising": "bastardizing",
116
+ "battleax": "battleaxe",
117
+ "baulk": "balk",
118
+ "baulked": "balked",
119
+ "baulking": "balking",
120
+ "baulks": "balks",
121
+ "bedevilled": "bedeviled",
122
+ "bedevilling": "bedeviling",
123
+ "behaviour": "behavior",
124
+ "behavioural": "behavioral",
125
+ "behaviourism": "behaviorism",
126
+ "behaviourist": "behaviorist",
127
+ "behaviourists": "behaviorists",
128
+ "behaviours": "behaviors",
129
+ "behove": "behoove",
130
+ "behoved": "behooved",
131
+ "behoves": "behooves",
132
+ "bejewelled": "bejeweled",
133
+ "belabour": "belabor",
134
+ "belaboured": "belabored",
135
+ "belabouring": "belaboring",
136
+ "belabours": "belabors",
137
+ "bevelled": "beveled",
138
+ "bevvies": "bevies",
139
+ "bevvy": "bevy",
140
+ "biassed": "biased",
141
+ "biassing": "biasing",
142
+ "bingeing": "binging",
143
+ "bougainvillaea": "bougainvillea",
144
+ "bougainvillaeas": "bougainvilleas",
145
+ "bowdlerise": "bowdlerize",
146
+ "bowdlerised": "bowdlerized",
147
+ "bowdlerises": "bowdlerizes",
148
+ "bowdlerising": "bowdlerizing",
149
+ "breathalyse": "breathalyze",
150
+ "breathalysed": "breathalyzed",
151
+ "breathalyser": "breathalyzer",
152
+ "breathalysers": "breathalyzers",
153
+ "breathalyses": "breathalyzes",
154
+ "breathalysing": "breathalyzing",
155
+ "brutalise": "brutalize",
156
+ "brutalised": "brutalized",
157
+ "brutalises": "brutalizes",
158
+ "brutalising": "brutalizing",
159
+ "busses": "buses",
160
+ "bussing": "busing",
161
+ "caesarean": "cesarean",
162
+ "caesareans": "cesareans",
163
+ "calibre": "caliber",
164
+ "calibres": "calibers",
165
+ "calliper": "caliper",
166
+ "callipers": "calipers",
167
+ "callisthenics": "calisthenics",
168
+ "canalise": "canalize",
169
+ "canalised": "canalized",
170
+ "canalises": "canalizes",
171
+ "canalising": "canalizing",
172
+ "cancelation": "cancellation",
173
+ "cancelations": "cancellations",
174
+ "cancelled": "canceled",
175
+ "cancelling": "canceling",
176
+ "candour": "candor",
177
+ "cannibalise": "cannibalize",
178
+ "cannibalised": "cannibalized",
179
+ "cannibalises": "cannibalizes",
180
+ "cannibalising": "cannibalizing",
181
+ "canonise": "canonize",
182
+ "canonised": "canonized",
183
+ "canonises": "canonizes",
184
+ "canonising": "canonizing",
185
+ "capitalise": "capitalize",
186
+ "capitalised": "capitalized",
187
+ "capitalises": "capitalizes",
188
+ "capitalising": "capitalizing",
189
+ "caramelise": "caramelize",
190
+ "caramelised": "caramelized",
191
+ "caramelises": "caramelizes",
192
+ "caramelising": "caramelizing",
193
+ "carbonise": "carbonize",
194
+ "carbonised": "carbonized",
195
+ "carbonises": "carbonizes",
196
+ "carbonising": "carbonizing",
197
+ "carolled": "caroled",
198
+ "carolling": "caroling",
199
+ "catalogue": "catalog",
200
+ "catalogued": "cataloged",
201
+ "catalogues": "catalogs",
202
+ "cataloguing": "cataloging",
203
+ "catalyse": "catalyze",
204
+ "catalysed": "catalyzed",
205
+ "catalyses": "catalyzes",
206
+ "catalysing": "catalyzing",
207
+ "categorise": "categorize",
208
+ "categorised": "categorized",
209
+ "categorises": "categorizes",
210
+ "categorising": "categorizing",
211
+ "cauterise": "cauterize",
212
+ "cauterised": "cauterized",
213
+ "cauterises": "cauterizes",
214
+ "cauterising": "cauterizing",
215
+ "cavilled": "caviled",
216
+ "cavilling": "caviling",
217
+ "centigramme": "centigram",
218
+ "centigrammes": "centigrams",
219
+ "centilitre": "centiliter",
220
+ "centilitres": "centiliters",
221
+ "centimetre": "centimeter",
222
+ "centimetres": "centimeters",
223
+ "centralise": "centralize",
224
+ "centralised": "centralized",
225
+ "centralises": "centralizes",
226
+ "centralising": "centralizing",
227
+ "centre": "center",
228
+ "centred": "centered",
229
+ "centrefold": "centerfold",
230
+ "centrefolds": "centerfolds",
231
+ "centrepiece": "centerpiece",
232
+ "centrepieces": "centerpieces",
233
+ "centres": "centers",
234
+ "channelled": "channeled",
235
+ "channelling": "channeling",
236
+ "characterise": "characterize",
237
+ "characterised": "characterized",
238
+ "characterises": "characterizes",
239
+ "characterising": "characterizing",
240
+ "cheque": "check",
241
+ "chequebook": "checkbook",
242
+ "chequebooks": "checkbooks",
243
+ "chequered": "checkered",
244
+ "cheques": "checks",
245
+ "chilli": "chili",
246
+ "chimaera": "chimera",
247
+ "chimaeras": "chimeras",
248
+ "chiselled": "chiseled",
249
+ "chiselling": "chiseling",
250
+ "circularise": "circularize",
251
+ "circularised": "circularized",
252
+ "circularises": "circularizes",
253
+ "circularising": "circularizing",
254
+ "civilise": "civilize",
255
+ "civilised": "civilized",
256
+ "civilises": "civilizes",
257
+ "civilising": "civilizing",
258
+ "clamour": "clamor",
259
+ "clamoured": "clamored",
260
+ "clamouring": "clamoring",
261
+ "clamours": "clamors",
262
+ "clangour": "clangor",
263
+ "clarinettist": "clarinetist",
264
+ "clarinettists": "clarinetists",
265
+ "collectivise": "collectivize",
266
+ "collectivised": "collectivized",
267
+ "collectivises": "collectivizes",
268
+ "collectivising": "collectivizing",
269
+ "colonisation": "colonization",
270
+ "colonise": "colonize",
271
+ "colonised": "colonized",
272
+ "coloniser": "colonizer",
273
+ "colonisers": "colonizers",
274
+ "colonises": "colonizes",
275
+ "colonising": "colonizing",
276
+ "colour": "color",
277
+ "colourant": "colorant",
278
+ "colourants": "colorants",
279
+ "coloured": "colored",
280
+ "coloureds": "coloreds",
281
+ "colourful": "colorful",
282
+ "colourfully": "colorfully",
283
+ "colouring": "coloring",
284
+ "colourize": "colorize",
285
+ "colourized": "colorized",
286
+ "colourizes": "colorizes",
287
+ "colourizing": "colorizing",
288
+ "colourless": "colorless",
289
+ "colours": "colors",
290
+ "commercialise": "commercialize",
291
+ "commercialised": "commercialized",
292
+ "commercialises": "commercializes",
293
+ "commercialising": "commercializing",
294
+ "compartmentalise": "compartmentalize",
295
+ "compartmentalised": "compartmentalized",
296
+ "compartmentalises": "compartmentalizes",
297
+ "compartmentalising": "compartmentalizing",
298
+ "computerise": "computerize",
299
+ "computerised": "computerized",
300
+ "computerises": "computerizes",
301
+ "computerising": "computerizing",
302
+ "conceptualise": "conceptualize",
303
+ "conceptualised": "conceptualized",
304
+ "conceptualises": "conceptualizes",
305
+ "conceptualising": "conceptualizing",
306
+ "connexion": "connection",
307
+ "connexions": "connections",
308
+ "contextualise": "contextualize",
309
+ "contextualised": "contextualized",
310
+ "contextualises": "contextualizes",
311
+ "contextualising": "contextualizing",
312
+ "cosier": "cozier",
313
+ "cosies": "cozies",
314
+ "cosiest": "coziest",
315
+ "cosily": "cozily",
316
+ "cosiness": "coziness",
317
+ "cosy": "cozy",
318
+ "councillor": "councilor",
319
+ "councillors": "councilors",
320
+ "counselled": "counseled",
321
+ "counselling": "counseling",
322
+ "counsellor": "counselor",
323
+ "counsellors": "counselors",
324
+ "crenelated": "crenellated",
325
+ "criminalise": "criminalize",
326
+ "criminalised": "criminalized",
327
+ "criminalises": "criminalizes",
328
+ "criminalising": "criminalizing",
329
+ "criticise": "criticize",
330
+ "criticised": "criticized",
331
+ "criticises": "criticizes",
332
+ "criticising": "criticizing",
333
+ "crueller": "crueler",
334
+ "cruellest": "cruelest",
335
+ "crystallisation": "crystallization",
336
+ "crystallise": "crystallize",
337
+ "crystallised": "crystallized",
338
+ "crystallises": "crystallizes",
339
+ "crystallising": "crystallizing",
340
+ "cudgelled": "cudgeled",
341
+ "cudgelling": "cudgeling",
342
+ "customise": "customize",
343
+ "customised": "customized",
344
+ "customises": "customizes",
345
+ "customising": "customizing",
346
+ "cypher": "cipher",
347
+ "cyphers": "ciphers",
348
+ "decentralisation": "decentralization",
349
+ "decentralise": "decentralize",
350
+ "decentralised": "decentralized",
351
+ "decentralises": "decentralizes",
352
+ "decentralising": "decentralizing",
353
+ "decriminalisation": "decriminalization",
354
+ "decriminalise": "decriminalize",
355
+ "decriminalised": "decriminalized",
356
+ "decriminalises": "decriminalizes",
357
+ "decriminalising": "decriminalizing",
358
+ "defence": "defense",
359
+ "defenceless": "defenseless",
360
+ "defences": "defenses",
361
+ "dehumanisation": "dehumanization",
362
+ "dehumanise": "dehumanize",
363
+ "dehumanised": "dehumanized",
364
+ "dehumanises": "dehumanizes",
365
+ "dehumanising": "dehumanizing",
366
+ "demeanour": "demeanor",
367
+ "demilitarisation": "demilitarization",
368
+ "demilitarise": "demilitarize",
369
+ "demilitarised": "demilitarized",
370
+ "demilitarises": "demilitarizes",
371
+ "demilitarising": "demilitarizing",
372
+ "demobilisation": "demobilization",
373
+ "demobilise": "demobilize",
374
+ "demobilised": "demobilized",
375
+ "demobilises": "demobilizes",
376
+ "demobilising": "demobilizing",
377
+ "democratisation": "democratization",
378
+ "democratise": "democratize",
379
+ "democratised": "democratized",
380
+ "democratises": "democratizes",
381
+ "democratising": "democratizing",
382
+ "demonise": "demonize",
383
+ "demonised": "demonized",
384
+ "demonises": "demonizes",
385
+ "demonising": "demonizing",
386
+ "demoralisation": "demoralization",
387
+ "demoralise": "demoralize",
388
+ "demoralised": "demoralized",
389
+ "demoralises": "demoralizes",
390
+ "demoralising": "demoralizing",
391
+ "denationalisation": "denationalization",
392
+ "denationalise": "denationalize",
393
+ "denationalised": "denationalized",
394
+ "denationalises": "denationalizes",
395
+ "denationalising": "denationalizing",
396
+ "deodorise": "deodorize",
397
+ "deodorised": "deodorized",
398
+ "deodorises": "deodorizes",
399
+ "deodorising": "deodorizing",
400
+ "depersonalise": "depersonalize",
401
+ "depersonalised": "depersonalized",
402
+ "depersonalises": "depersonalizes",
403
+ "depersonalising": "depersonalizing",
404
+ "deputise": "deputize",
405
+ "deputised": "deputized",
406
+ "deputises": "deputizes",
407
+ "deputising": "deputizing",
408
+ "desensitisation": "desensitization",
409
+ "desensitise": "desensitize",
410
+ "desensitised": "desensitized",
411
+ "desensitises": "desensitizes",
412
+ "desensitising": "desensitizing",
413
+ "destabilisation": "destabilization",
414
+ "destabilise": "destabilize",
415
+ "destabilised": "destabilized",
416
+ "destabilises": "destabilizes",
417
+ "destabilising": "destabilizing",
418
+ "dialled": "dialed",
419
+ "dialling": "dialing",
420
+ "dialogue": "dialog",
421
+ "dialogues": "dialogs",
422
+ "diarrhoea": "diarrhea",
423
+ "digitise": "digitize",
424
+ "digitised": "digitized",
425
+ "digitises": "digitizes",
426
+ "digitising": "digitizing",
427
+ "disc": "disk",
428
+ "discolour": "discolor",
429
+ "discoloured": "discolored",
430
+ "discolouring": "discoloring",
431
+ "discolours": "discolors",
432
+ "discs": "disks",
433
+ "disembowelled": "disemboweled",
434
+ "disembowelling": "disemboweling",
435
+ "disfavour": "disfavor",
436
+ "dishevelled": "disheveled",
437
+ "dishonour": "dishonor",
438
+ "dishonourable": "dishonorable",
439
+ "dishonourably": "dishonorably",
440
+ "dishonoured": "dishonored",
441
+ "dishonouring": "dishonoring",
442
+ "dishonours": "dishonors",
443
+ "disorganisation": "disorganization",
444
+ "disorganised": "disorganized",
445
+ "distil": "distill",
446
+ "distils": "distills",
447
+ "dramatisation": "dramatization",
448
+ "dramatisations": "dramatizations",
449
+ "dramatise": "dramatize",
450
+ "dramatised": "dramatized",
451
+ "dramatises": "dramatizes",
452
+ "dramatising": "dramatizing",
453
+ "draught": "draft",
454
+ "draughtboard": "draftboard",
455
+ "draughtboards": "draftboards",
456
+ "draughtier": "draftier",
457
+ "draughtiest": "draftiest",
458
+ "draughts": "drafts",
459
+ "draughtsman": "draftsman",
460
+ "draughtsmanship": "draftsmanship",
461
+ "draughtsmen": "draftsmen",
462
+ "draughtswoman": "draftswoman",
463
+ "draughtswomen": "draftswomen",
464
+ "draughty": "drafty",
465
+ "drivelled": "driveled",
466
+ "drivelling": "driveling",
467
+ "duelled": "dueled",
468
+ "duelling": "dueling",
469
+ "economise": "economize",
470
+ "economised": "economized",
471
+ "economises": "economizes",
472
+ "economising": "economizing",
473
+ "editorialise": "editorialize",
474
+ "editorialised": "editorialized",
475
+ "editorialises": "editorializes",
476
+ "editorialising": "editorializing",
477
+ "edoema": "edema",
478
+ "empathise": "empathize",
479
+ "empathised": "empathized",
480
+ "empathises": "empathizes",
481
+ "empathising": "empathizing",
482
+ "emphasise": "emphasize",
483
+ "emphasised": "emphasized",
484
+ "emphasises": "emphasizes",
485
+ "emphasising": "emphasizing",
486
+ "enamelled": "enameled",
487
+ "enamelling": "enameling",
488
+ "enamoured": "enamored",
489
+ "encyclopaedia": "encyclopedia",
490
+ "encyclopaedias": "encyclopedias",
491
+ "encyclopaedic": "encyclopedic",
492
+ "endeavour": "endeavor",
493
+ "endeavoured": "endeavored",
494
+ "endeavouring": "endeavoring",
495
+ "endeavours": "endeavors",
496
+ "energise": "energize",
497
+ "energised": "energized",
498
+ "energises": "energizes",
499
+ "energising": "energizing",
500
+ "enrol": "enroll",
501
+ "enrols": "enrolls",
502
+ "enthral": "enthrall",
503
+ "enthrals": "enthralls",
504
+ "epaulette": "epaulet",
505
+ "epaulettes": "epaulets",
506
+ "epicentre": "epicenter",
507
+ "epicentres": "epicenters",
508
+ "epilogue": "epilog",
509
+ "epilogues": "epilogs",
510
+ "epitomise": "epitomize",
511
+ "epitomised": "epitomized",
512
+ "epitomises": "epitomizes",
513
+ "epitomising": "epitomizing",
514
+ "equalisation": "equalization",
515
+ "equalise": "equalize",
516
+ "equalised": "equalized",
517
+ "equaliser": "equalizer",
518
+ "equalisers": "equalizers",
519
+ "equalises": "equalizes",
520
+ "equalising": "equalizing",
521
+ "eulogise": "eulogize",
522
+ "eulogised": "eulogized",
523
+ "eulogises": "eulogizes",
524
+ "eulogising": "eulogizing",
525
+ "evangelise": "evangelize",
526
+ "evangelised": "evangelized",
527
+ "evangelises": "evangelizes",
528
+ "evangelising": "evangelizing",
529
+ "exorcise": "exorcize",
530
+ "exorcised": "exorcized",
531
+ "exorcises": "exorcizes",
532
+ "exorcising": "exorcizing",
533
+ "extemporisation": "extemporization",
534
+ "extemporise": "extemporize",
535
+ "extemporised": "extemporized",
536
+ "extemporises": "extemporizes",
537
+ "extemporising": "extemporizing",
538
+ "externalisation": "externalization",
539
+ "externalisations": "externalizations",
540
+ "externalise": "externalize",
541
+ "externalised": "externalized",
542
+ "externalises": "externalizes",
543
+ "externalising": "externalizing",
544
+ "factorise": "factorize",
545
+ "factorised": "factorized",
546
+ "factorises": "factorizes",
547
+ "factorising": "factorizing",
548
+ "faecal": "fecal",
549
+ "faeces": "feces",
550
+ "familiarisation": "familiarization",
551
+ "familiarise": "familiarize",
552
+ "familiarised": "familiarized",
553
+ "familiarises": "familiarizes",
554
+ "familiarising": "familiarizing",
555
+ "fantasise": "fantasize",
556
+ "fantasised": "fantasized",
557
+ "fantasises": "fantasizes",
558
+ "fantasising": "fantasizing",
559
+ "favour": "favor",
560
+ "favourable": "favorable",
561
+ "favourably": "favorably",
562
+ "favoured": "favored",
563
+ "favouring": "favoring",
564
+ "favourite": "favorite",
565
+ "favourites": "favorites",
566
+ "favouritism": "favoritism",
567
+ "favours": "favors",
568
+ "feminise": "feminize",
569
+ "feminised": "feminized",
570
+ "feminises": "feminizes",
571
+ "feminising": "feminizing",
572
+ "fertilisation": "fertilization",
573
+ "fertilise": "fertilize",
574
+ "fertilised": "fertilized",
575
+ "fertiliser": "fertilizer",
576
+ "fertilisers": "fertilizers",
577
+ "fertilises": "fertilizes",
578
+ "fertilising": "fertilizing",
579
+ "fervour": "fervor",
580
+ "fibre": "fiber",
581
+ "fibreglass": "fiberglass",
582
+ "fibres": "fibers",
583
+ "fictionalisation": "fictionalization",
584
+ "fictionalisations": "fictionalizations",
585
+ "fictionalise": "fictionalize",
586
+ "fictionalised": "fictionalized",
587
+ "fictionalises": "fictionalizes",
588
+ "fictionalising": "fictionalizing",
589
+ "fillet": "filet",
590
+ "filleted": "fileted",
591
+ "filleting": "fileting",
592
+ "fillets": "filets",
593
+ "finalisation": "finalization",
594
+ "finalise": "finalize",
595
+ "finalised": "finalized",
596
+ "finalises": "finalizes",
597
+ "finalising": "finalizing",
598
+ "flautist": "flutist",
599
+ "flautists": "flutists",
600
+ "flavour": "flavor",
601
+ "flavoured": "flavored",
602
+ "flavouring": "flavoring",
603
+ "flavourings": "flavorings",
604
+ "flavourless": "flavorless",
605
+ "flavours": "flavors",
606
+ "flavoursome": "flavorsome",
607
+ "flyer / flier": "flier / flyer",
608
+ "foetal": "fetal",
609
+ "foetid": "fetid",
610
+ "foetus": "fetus",
611
+ "foetuses": "fetuses",
612
+ "formalisation": "formalization",
613
+ "formalise": "formalize",
614
+ "formalised": "formalized",
615
+ "formalises": "formalizes",
616
+ "formalising": "formalizing",
617
+ "fossilisation": "fossilization",
618
+ "fossilise": "fossilize",
619
+ "fossilised": "fossilized",
620
+ "fossilises": "fossilizes",
621
+ "fossilising": "fossilizing",
622
+ "fraternisation": "fraternization",
623
+ "fraternise": "fraternize",
624
+ "fraternised": "fraternized",
625
+ "fraternises": "fraternizes",
626
+ "fraternising": "fraternizing",
627
+ "fulfil": "fulfill",
628
+ "fulfilment": "fulfillment",
629
+ "fulfils": "fulfills",
630
+ "funnelled": "funneled",
631
+ "funnelling": "funneling",
632
+ "gage": "gauge",
633
+ "gaged": "gauged",
634
+ "gages": "gauges",
635
+ "gaging": "gauging",
636
+ "galvanise": "galvanize",
637
+ "galvanised": "galvanized",
638
+ "galvanises": "galvanizes",
639
+ "galvanising": "galvanizing",
640
+ "gambolled": "gamboled",
641
+ "gambolling": "gamboling",
642
+ "gaol": "jail",
643
+ "gaolbird": "jailbird",
644
+ "gaolbirds": "jailbirds",
645
+ "gaolbreak": "jailbreak",
646
+ "gaolbreaks": "jailbreaks",
647
+ "gaoled": "jailed",
648
+ "gaoler": "jailer",
649
+ "gaolers": "jailers",
650
+ "gaoling": "jailing",
651
+ "gaols": "jails",
652
+ "gasses": "gases",
653
+ "generalisation": "generalization",
654
+ "generalisations": "generalizations",
655
+ "generalise": "generalize",
656
+ "generalised": "generalized",
657
+ "generalises": "generalizes",
658
+ "generalising": "generalizing",
659
+ "ghettoise": "ghettoize",
660
+ "ghettoised": "ghettoized",
661
+ "ghettoises": "ghettoizes",
662
+ "ghettoising": "ghettoizing",
663
+ "gipsies": "gypsies",
664
+ "glamor": "glamour",
665
+ "glamorise": "glamorize",
666
+ "glamorised": "glamorized",
667
+ "glamorises": "glamorizes",
668
+ "glamorising": "glamorizing",
669
+ "globalisation": "globalization",
670
+ "globalise": "globalize",
671
+ "globalised": "globalized",
672
+ "globalises": "globalizes",
673
+ "globalising": "globalizing",
674
+ "glueing": "gluing",
675
+ "goitre": "goiter",
676
+ "goitres": "goiters",
677
+ "gonorrhoea": "gonorrhea",
678
+ "gramme": "gram",
679
+ "grammes": "grams",
680
+ "gravelled": "graveled",
681
+ "grey": "gray",
682
+ "greyed": "grayed",
683
+ "greying": "graying",
684
+ "greyish": "grayish",
685
+ "greyness": "grayness",
686
+ "greys": "grays",
687
+ "grovelled": "groveled",
688
+ "grovelling": "groveling",
689
+ "groyne": "groin",
690
+ "groynes": "groins",
691
+ "gruelling": "grueling",
692
+ "gruellingly": "gruelingly",
693
+ "gryphon": "griffin",
694
+ "gryphons": "griffins",
695
+ "gynaecological": "gynecological",
696
+ "gynaecologist": "gynecologist",
697
+ "gynaecologists": "gynecologists",
698
+ "gynaecology": "gynecology",
699
+ "haematological": "hematological",
700
+ "haematologist": "hematologist",
701
+ "haematologists": "hematologists",
702
+ "haematology": "hematology",
703
+ "haemoglobin": "hemoglobin",
704
+ "haemophilia": "hemophilia",
705
+ "haemophiliac": "hemophiliac",
706
+ "haemophiliacs": "hemophiliacs",
707
+ "haemorrhage": "hemorrhage",
708
+ "haemorrhaged": "hemorrhaged",
709
+ "haemorrhages": "hemorrhages",
710
+ "haemorrhaging": "hemorrhaging",
711
+ "haemorrhoids": "hemorrhoids",
712
+ "harbour": "harbor",
713
+ "harboured": "harbored",
714
+ "harbouring": "harboring",
715
+ "harbours": "harbors",
716
+ "harmonisation": "harmonization",
717
+ "harmonise": "harmonize",
718
+ "harmonised": "harmonized",
719
+ "harmonises": "harmonizes",
720
+ "harmonising": "harmonizing",
721
+ "homoeopath": "homeopath",
722
+ "homoeopathic": "homeopathic",
723
+ "homoeopaths": "homeopaths",
724
+ "homoeopathy": "homeopathy",
725
+ "homogenise": "homogenize",
726
+ "homogenised": "homogenized",
727
+ "homogenises": "homogenizes",
728
+ "homogenising": "homogenizing",
729
+ "honour": "honor",
730
+ "honourable": "honorable",
731
+ "honourably": "honorably",
732
+ "honoured": "honored",
733
+ "honouring": "honoring",
734
+ "honours": "honors",
735
+ "hospitalisation": "hospitalization",
736
+ "hospitalise": "hospitalize",
737
+ "hospitalised": "hospitalized",
738
+ "hospitalises": "hospitalizes",
739
+ "hospitalising": "hospitalizing",
740
+ "humanise": "humanize",
741
+ "humanised": "humanized",
742
+ "humanises": "humanizes",
743
+ "humanising": "humanizing",
744
+ "humour": "humor",
745
+ "humoured": "humored",
746
+ "humouring": "humoring",
747
+ "humourless": "humorless",
748
+ "humours": "humors",
749
+ "hybridise": "hybridize",
750
+ "hybridised": "hybridized",
751
+ "hybridises": "hybridizes",
752
+ "hybridising": "hybridizing",
753
+ "hypnotise": "hypnotize",
754
+ "hypnotised": "hypnotized",
755
+ "hypnotises": "hypnotizes",
756
+ "hypnotising": "hypnotizing",
757
+ "hypothesise": "hypothesize",
758
+ "hypothesised": "hypothesized",
759
+ "hypothesises": "hypothesizes",
760
+ "hypothesising": "hypothesizing",
761
+ "idealisation": "idealization",
762
+ "idealise": "idealize",
763
+ "idealised": "idealized",
764
+ "idealises": "idealizes",
765
+ "idealising": "idealizing",
766
+ "idolise": "idolize",
767
+ "idolised": "idolized",
768
+ "idolises": "idolizes",
769
+ "idolising": "idolizing",
770
+ "immobilisation": "immobilization",
771
+ "immobilise": "immobilize",
772
+ "immobilised": "immobilized",
773
+ "immobiliser": "immobilizer",
774
+ "immobilisers": "immobilizers",
775
+ "immobilises": "immobilizes",
776
+ "immobilising": "immobilizing",
777
+ "immortalise": "immortalize",
778
+ "immortalised": "immortalized",
779
+ "immortalises": "immortalizes",
780
+ "immortalising": "immortalizing",
781
+ "immunisation": "immunization",
782
+ "immunise": "immunize",
783
+ "immunised": "immunized",
784
+ "immunises": "immunizes",
785
+ "immunising": "immunizing",
786
+ "impanelled": "impaneled",
787
+ "impanelling": "impaneling",
788
+ "imperilled": "imperiled",
789
+ "imperilling": "imperiling",
790
+ "individualise": "individualize",
791
+ "individualised": "individualized",
792
+ "individualises": "individualizes",
793
+ "individualising": "individualizing",
794
+ "industrialise": "industrialize",
795
+ "industrialised": "industrialized",
796
+ "industrialises": "industrializes",
797
+ "industrialising": "industrializing",
798
+ "inflexion": "inflection",
799
+ "inflexions": "inflections",
800
+ "initialise": "initialize",
801
+ "initialised": "initialized",
802
+ "initialises": "initializes",
803
+ "initialising": "initializing",
804
+ "initialled": "initialed",
805
+ "initialling": "initialing",
806
+ "instal": "install",
807
+ "instalment": "installment",
808
+ "instalments": "installments",
809
+ "instals": "installs",
810
+ "instil": "instill",
811
+ "instils": "instills",
812
+ "institutionalisation": "institutionalization",
813
+ "institutionalise": "institutionalize",
814
+ "institutionalised": "institutionalized",
815
+ "institutionalises": "institutionalizes",
816
+ "institutionalising": "institutionalizing",
817
+ "intellectualise": "intellectualize",
818
+ "intellectualised": "intellectualized",
819
+ "intellectualises": "intellectualizes",
820
+ "intellectualising": "intellectualizing",
821
+ "internalisation": "internalization",
822
+ "internalise": "internalize",
823
+ "internalised": "internalized",
824
+ "internalises": "internalizes",
825
+ "internalising": "internalizing",
826
+ "internationalisation": "internationalization",
827
+ "internationalise": "internationalize",
828
+ "internationalised": "internationalized",
829
+ "internationalises": "internationalizes",
830
+ "internationalising": "internationalizing",
831
+ "ionisation": "ionization",
832
+ "ionise": "ionize",
833
+ "ionised": "ionized",
834
+ "ioniser": "ionizer",
835
+ "ionisers": "ionizers",
836
+ "ionises": "ionizes",
837
+ "ionising": "ionizing",
838
+ "italicise": "italicize",
839
+ "italicised": "italicized",
840
+ "italicises": "italicizes",
841
+ "italicising": "italicizing",
842
+ "itemise": "itemize",
843
+ "itemised": "itemized",
844
+ "itemises": "itemizes",
845
+ "itemising": "itemizing",
846
+ "jeopardise": "jeopardize",
847
+ "jeopardised": "jeopardized",
848
+ "jeopardises": "jeopardizes",
849
+ "jeopardising": "jeopardizing",
850
+ "jewelled": "jeweled",
851
+ "jeweller": "jeweler",
852
+ "jewellers": "jewelers",
853
+ "jewellery": "jewelry",
854
+ "judgement": "judgment",
855
+ "kilogramme": "kilogram",
856
+ "kilogrammes": "kilograms",
857
+ "kilometre": "kilometer",
858
+ "kilometres": "kilometers",
859
+ "labelled": "labeled",
860
+ "labelling": "labeling",
861
+ "labour": "labor",
862
+ "laboured": "labored",
863
+ "labourer": "laborer",
864
+ "labourers": "laborers",
865
+ "labouring": "laboring",
866
+ "labours": "labors",
867
+ "lacklustre": "lackluster",
868
+ "legalisation": "legalization",
869
+ "legalise": "legalize",
870
+ "legalised": "legalized",
871
+ "legalises": "legalizes",
872
+ "legalising": "legalizing",
873
+ "legitimise": "legitimize",
874
+ "legitimised": "legitimized",
875
+ "legitimises": "legitimizes",
876
+ "legitimising": "legitimizing",
877
+ "leukaemia": "leukemia",
878
+ "levelled": "leveled",
879
+ "leveller": "leveler",
880
+ "levellers": "levelers",
881
+ "levelling": "leveling",
882
+ "libelled": "libeled",
883
+ "libelling": "libeling",
884
+ "libellous": "libelous",
885
+ "liberalisation": "liberalization",
886
+ "liberalise": "liberalize",
887
+ "liberalised": "liberalized",
888
+ "liberalises": "liberalizes",
889
+ "liberalising": "liberalizing",
890
+ "licence": "license",
891
+ "licenced": "licensed",
892
+ "licences": "licenses",
893
+ "licencing": "licensing",
894
+ "likeable": "likable",
895
+ "lionisation": "lionization",
896
+ "lionise": "lionize",
897
+ "lionised": "lionized",
898
+ "lionises": "lionizes",
899
+ "lionising": "lionizing",
900
+ "liquidise": "liquidize",
901
+ "liquidised": "liquidized",
902
+ "liquidiser": "liquidizer",
903
+ "liquidisers": "liquidizers",
904
+ "liquidises": "liquidizes",
905
+ "liquidising": "liquidizing",
906
+ "litre": "liter",
907
+ "litres": "liters",
908
+ "localise": "localize",
909
+ "localised": "localized",
910
+ "localises": "localizes",
911
+ "localising": "localizing",
912
+ "louvre": "louver",
913
+ "louvred": "louvered",
914
+ "louvres": "louvers",
915
+ "lustre": "luster",
916
+ "magnetise": "magnetize",
917
+ "magnetised": "magnetized",
918
+ "magnetises": "magnetizes",
919
+ "magnetising": "magnetizing",
920
+ "manoeuvrability": "maneuverability",
921
+ "manoeuvrable": "maneuverable",
922
+ "manoeuvre": "maneuver",
923
+ "manoeuvred": "maneuvered",
924
+ "manoeuvres": "maneuvers",
925
+ "manoeuvring": "maneuvering",
926
+ "manoeuvrings": "maneuverings",
927
+ "marginalisation": "marginalization",
928
+ "marginalise": "marginalize",
929
+ "marginalised": "marginalized",
930
+ "marginalises": "marginalizes",
931
+ "marginalising": "marginalizing",
932
+ "marshalled": "marshaled",
933
+ "marshalling": "marshaling",
934
+ "marvelled": "marveled",
935
+ "marvelling": "marveling",
936
+ "marvellous": "marvelous",
937
+ "marvellously": "marvelously",
938
+ "materialisation": "materialization",
939
+ "materialise": "materialize",
940
+ "materialised": "materialized",
941
+ "materialises": "materializes",
942
+ "materialising": "materializing",
943
+ "maximisation": "maximization",
944
+ "maximise": "maximize",
945
+ "maximised": "maximized",
946
+ "maximises": "maximizes",
947
+ "maximising": "maximizing",
948
+ "meagre": "meager",
949
+ "mechanisation": "mechanization",
950
+ "mechanise": "mechanize",
951
+ "mechanised": "mechanized",
952
+ "mechanises": "mechanizes",
953
+ "mechanising": "mechanizing",
954
+ "mediaeval": "medieval",
955
+ "memorialise": "memorialize",
956
+ "memorialised": "memorialized",
957
+ "memorialises": "memorializes",
958
+ "memorialising": "memorializing",
959
+ "memorise": "memorize",
960
+ "memorised": "memorized",
961
+ "memorises": "memorizes",
962
+ "memorising": "memorizing",
963
+ "mesmerise": "mesmerize",
964
+ "mesmerised": "mesmerized",
965
+ "mesmerises": "mesmerizes",
966
+ "mesmerising": "mesmerizing",
967
+ "metabolise": "metabolize",
968
+ "metabolised": "metabolized",
969
+ "metabolises": "metabolizes",
970
+ "metabolising": "metabolizing",
971
+ "metre": "meter",
972
+ "metres": "meters",
973
+ "mhm": "hmm",
974
+ "micrometre": "micrometer",
975
+ "micrometres": "micrometers",
976
+ "militarise": "militarize",
977
+ "militarised": "militarized",
978
+ "militarises": "militarizes",
979
+ "militarising": "militarizing",
980
+ "milligramme": "milligram",
981
+ "milligrammes": "milligrams",
982
+ "millilitre": "milliliter",
983
+ "millilitres": "milliliters",
984
+ "millimetre": "millimeter",
985
+ "millimetres": "millimeters",
986
+ "miniaturisation": "miniaturization",
987
+ "miniaturise": "miniaturize",
988
+ "miniaturised": "miniaturized",
989
+ "miniaturises": "miniaturizes",
990
+ "miniaturising": "miniaturizing",
991
+ "minibusses": "minibuses",
992
+ "minimise": "minimize",
993
+ "minimised": "minimized",
994
+ "minimises": "minimizes",
995
+ "minimising": "minimizing",
996
+ "misbehaviour": "misbehavior",
997
+ "misdemeanour": "misdemeanor",
998
+ "misdemeanours": "misdemeanors",
999
+ "misspelt": "misspelled",
1000
+ "mitre": "miter",
1001
+ "mitres": "miters",
1002
+ "mm": "hmm",
1003
+ "mmm": "hmm",
1004
+ "mobilisation": "mobilization",
1005
+ "mobilise": "mobilize",
1006
+ "mobilised": "mobilized",
1007
+ "mobilises": "mobilizes",
1008
+ "mobilising": "mobilizing",
1009
+ "modelled": "modeled",
1010
+ "modeller": "modeler",
1011
+ "modellers": "modelers",
1012
+ "modelling": "modeling",
1013
+ "modernise": "modernize",
1014
+ "modernised": "modernized",
1015
+ "modernises": "modernizes",
1016
+ "modernising": "modernizing",
1017
+ "moisturise": "moisturize",
1018
+ "moisturised": "moisturized",
1019
+ "moisturiser": "moisturizer",
1020
+ "moisturisers": "moisturizers",
1021
+ "moisturises": "moisturizes",
1022
+ "moisturising": "moisturizing",
1023
+ "monologue": "monolog",
1024
+ "monologues": "monologs",
1025
+ "monopolisation": "monopolization",
1026
+ "monopolise": "monopolize",
1027
+ "monopolised": "monopolized",
1028
+ "monopolises": "monopolizes",
1029
+ "monopolising": "monopolizing",
1030
+ "moralise": "moralize",
1031
+ "moralised": "moralized",
1032
+ "moralises": "moralizes",
1033
+ "moralising": "moralizing",
1034
+ "motorised": "motorized",
1035
+ "mould": "mold",
1036
+ "moulded": "molded",
1037
+ "moulder": "molder",
1038
+ "mouldered": "moldered",
1039
+ "mouldering": "moldering",
1040
+ "moulders": "molders",
1041
+ "mouldier": "moldier",
1042
+ "mouldiest": "moldiest",
1043
+ "moulding": "molding",
1044
+ "mouldings": "moldings",
1045
+ "moulds": "molds",
1046
+ "mouldy": "moldy",
1047
+ "moult": "molt",
1048
+ "moulted": "molted",
1049
+ "moulting": "molting",
1050
+ "moults": "molts",
1051
+ "moustache": "mustache",
1052
+ "moustached": "mustached",
1053
+ "moustaches": "mustaches",
1054
+ "moustachioed": "mustachioed",
1055
+ "multicoloured": "multicolored",
1056
+ "nationalisation": "nationalization",
1057
+ "nationalisations": "nationalizations",
1058
+ "nationalise": "nationalize",
1059
+ "nationalised": "nationalized",
1060
+ "nationalises": "nationalizes",
1061
+ "nationalising": "nationalizing",
1062
+ "naturalisation": "naturalization",
1063
+ "naturalise": "naturalize",
1064
+ "naturalised": "naturalized",
1065
+ "naturalises": "naturalizes",
1066
+ "naturalising": "naturalizing",
1067
+ "neighbour": "neighbor",
1068
+ "neighbourhood": "neighborhood",
1069
+ "neighbourhoods": "neighborhoods",
1070
+ "neighbouring": "neighboring",
1071
+ "neighbourliness": "neighborliness",
1072
+ "neighbourly": "neighborly",
1073
+ "neighbours": "neighbors",
1074
+ "neutralisation": "neutralization",
1075
+ "neutralise": "neutralize",
1076
+ "neutralised": "neutralized",
1077
+ "neutralises": "neutralizes",
1078
+ "neutralising": "neutralizing",
1079
+ "normalisation": "normalization",
1080
+ "normalise": "normalize",
1081
+ "normalised": "normalized",
1082
+ "normalises": "normalizes",
1083
+ "normalising": "normalizing",
1084
+ "odour": "odor",
1085
+ "odourless": "odorless",
1086
+ "odours": "odors",
1087
+ "oesophagus": "esophagus",
1088
+ "oesophaguses": "esophaguses",
1089
+ "oestrogen": "estrogen",
1090
+ "offence": "offense",
1091
+ "offences": "offenses",
1092
+ "omelette": "omelet",
1093
+ "omelettes": "omelets",
1094
+ "optimise": "optimize",
1095
+ "optimised": "optimized",
1096
+ "optimises": "optimizes",
1097
+ "optimising": "optimizing",
1098
+ "organisation": "organization",
1099
+ "organisational": "organizational",
1100
+ "organisations": "organizations",
1101
+ "organise": "organize",
1102
+ "organised": "organized",
1103
+ "organiser": "organizer",
1104
+ "organisers": "organizers",
1105
+ "organises": "organizes",
1106
+ "organising": "organizing",
1107
+ "orthopaedic": "orthopedic",
1108
+ "orthopaedics": "orthopedics",
1109
+ "ostracise": "ostracize",
1110
+ "ostracised": "ostracized",
1111
+ "ostracises": "ostracizes",
1112
+ "ostracising": "ostracizing",
1113
+ "outmanoeuvre": "outmaneuver",
1114
+ "outmanoeuvred": "outmaneuvered",
1115
+ "outmanoeuvres": "outmaneuvers",
1116
+ "outmanoeuvring": "outmaneuvering",
1117
+ "overemphasise": "overemphasize",
1118
+ "overemphasised": "overemphasized",
1119
+ "overemphasises": "overemphasizes",
1120
+ "overemphasising": "overemphasizing",
1121
+ "oxidisation": "oxidization",
1122
+ "oxidise": "oxidize",
1123
+ "oxidised": "oxidized",
1124
+ "oxidises": "oxidizes",
1125
+ "oxidising": "oxidizing",
1126
+ "paederast": "pederast",
1127
+ "paederasts": "pederasts",
1128
+ "paediatric": "pediatric",
1129
+ "paediatrician": "pediatrician",
1130
+ "paediatricians": "pediatricians",
1131
+ "paediatrics": "pediatrics",
1132
+ "paedophile": "pedophile",
1133
+ "paedophiles": "pedophiles",
1134
+ "paedophilia": "pedophilia",
1135
+ "palaeolithic": "paleolithic",
1136
+ "palaeontologist": "paleontologist",
1137
+ "palaeontologists": "paleontologists",
1138
+ "palaeontology": "paleontology",
1139
+ "panelled": "paneled",
1140
+ "panelling": "paneling",
1141
+ "panellist": "panelist",
1142
+ "panellists": "panelists",
1143
+ "paralyse": "paralyze",
1144
+ "paralysed": "paralyzed",
1145
+ "paralyses": "paralyzes",
1146
+ "paralysing": "paralyzing",
1147
+ "parcelled": "parceled",
1148
+ "parcelling": "parceling",
1149
+ "parlour": "parlor",
1150
+ "parlours": "parlors",
1151
+ "particularise": "particularize",
1152
+ "particularised": "particularized",
1153
+ "particularises": "particularizes",
1154
+ "particularising": "particularizing",
1155
+ "passivisation": "passivization",
1156
+ "passivise": "passivize",
1157
+ "passivised": "passivized",
1158
+ "passivises": "passivizes",
1159
+ "passivising": "passivizing",
1160
+ "pasteurisation": "pasteurization",
1161
+ "pasteurise": "pasteurize",
1162
+ "pasteurised": "pasteurized",
1163
+ "pasteurises": "pasteurizes",
1164
+ "pasteurising": "pasteurizing",
1165
+ "patronise": "patronize",
1166
+ "patronised": "patronized",
1167
+ "patronises": "patronizes",
1168
+ "patronising": "patronizing",
1169
+ "patronisingly": "patronizingly",
1170
+ "pedalled": "pedaled",
1171
+ "pedalling": "pedaling",
1172
+ "pedestrianisation": "pedestrianization",
1173
+ "pedestrianise": "pedestrianize",
1174
+ "pedestrianised": "pedestrianized",
1175
+ "pedestrianises": "pedestrianizes",
1176
+ "pedestrianising": "pedestrianizing",
1177
+ "penalise": "penalize",
1178
+ "penalised": "penalized",
1179
+ "penalises": "penalizes",
1180
+ "penalising": "penalizing",
1181
+ "pencilled": "penciled",
1182
+ "pencilling": "penciling",
1183
+ "personalise": "personalize",
1184
+ "personalised": "personalized",
1185
+ "personalises": "personalizes",
1186
+ "personalising": "personalizing",
1187
+ "pharmacopoeia": "pharmacopeia",
1188
+ "pharmacopoeias": "pharmacopeias",
1189
+ "philosophise": "philosophize",
1190
+ "philosophised": "philosophized",
1191
+ "philosophises": "philosophizes",
1192
+ "philosophising": "philosophizing",
1193
+ "philtre": "filter",
1194
+ "philtres": "filters",
1195
+ "phoney": "phony",
1196
+ "plagiarise": "plagiarize",
1197
+ "plagiarised": "plagiarized",
1198
+ "plagiarises": "plagiarizes",
1199
+ "plagiarising": "plagiarizing",
1200
+ "plough": "plow",
1201
+ "ploughed": "plowed",
1202
+ "ploughing": "plowing",
1203
+ "ploughman": "plowman",
1204
+ "ploughmen": "plowmen",
1205
+ "ploughs": "plows",
1206
+ "ploughshare": "plowshare",
1207
+ "ploughshares": "plowshares",
1208
+ "polarisation": "polarization",
1209
+ "polarise": "polarize",
1210
+ "polarised": "polarized",
1211
+ "polarises": "polarizes",
1212
+ "polarising": "polarizing",
1213
+ "politicisation": "politicization",
1214
+ "politicise": "politicize",
1215
+ "politicised": "politicized",
1216
+ "politicises": "politicizes",
1217
+ "politicising": "politicizing",
1218
+ "popularisation": "popularization",
1219
+ "popularise": "popularize",
1220
+ "popularised": "popularized",
1221
+ "popularises": "popularizes",
1222
+ "popularising": "popularizing",
1223
+ "pouffe": "pouf",
1224
+ "pouffes": "poufs",
1225
+ "practise": "practice",
1226
+ "practised": "practiced",
1227
+ "practises": "practices",
1228
+ "practising": "practicing",
1229
+ "praesidium": "presidium",
1230
+ "praesidiums": "presidiums",
1231
+ "pressurisation": "pressurization",
1232
+ "pressurise": "pressurize",
1233
+ "pressurised": "pressurized",
1234
+ "pressurises": "pressurizes",
1235
+ "pressurising": "pressurizing",
1236
+ "pretence": "pretense",
1237
+ "pretences": "pretenses",
1238
+ "primaeval": "primeval",
1239
+ "prioritisation": "prioritization",
1240
+ "prioritise": "prioritize",
1241
+ "prioritised": "prioritized",
1242
+ "prioritises": "prioritizes",
1243
+ "prioritising": "prioritizing",
1244
+ "privatisation": "privatization",
1245
+ "privatisations": "privatizations",
1246
+ "privatise": "privatize",
1247
+ "privatised": "privatized",
1248
+ "privatises": "privatizes",
1249
+ "privatising": "privatizing",
1250
+ "professionalisation": "professionalization",
1251
+ "professionalise": "professionalize",
1252
+ "professionalised": "professionalized",
1253
+ "professionalises": "professionalizes",
1254
+ "professionalising": "professionalizing",
1255
+ "programme": "program",
1256
+ "programmes": "programs",
1257
+ "prologue": "prolog",
1258
+ "prologues": "prologs",
1259
+ "propagandise": "propagandize",
1260
+ "propagandised": "propagandized",
1261
+ "propagandises": "propagandizes",
1262
+ "propagandising": "propagandizing",
1263
+ "proselytise": "proselytize",
1264
+ "proselytised": "proselytized",
1265
+ "proselytiser": "proselytizer",
1266
+ "proselytisers": "proselytizers",
1267
+ "proselytises": "proselytizes",
1268
+ "proselytising": "proselytizing",
1269
+ "psychoanalyse": "psychoanalyze",
1270
+ "psychoanalysed": "psychoanalyzed",
1271
+ "psychoanalyses": "psychoanalyzes",
1272
+ "psychoanalysing": "psychoanalyzing",
1273
+ "publicise": "publicize",
1274
+ "publicised": "publicized",
1275
+ "publicises": "publicizes",
1276
+ "publicising": "publicizing",
1277
+ "pulverisation": "pulverization",
1278
+ "pulverise": "pulverize",
1279
+ "pulverised": "pulverized",
1280
+ "pulverises": "pulverizes",
1281
+ "pulverising": "pulverizing",
1282
+ "pummelled": "pummel",
1283
+ "pummelling": "pummeled",
1284
+ "pyjama": "pajama",
1285
+ "pyjamas": "pajamas",
1286
+ "pzazz": "pizzazz",
1287
+ "quarrelled": "quarreled",
1288
+ "quarrelling": "quarreling",
1289
+ "radicalise": "radicalize",
1290
+ "radicalised": "radicalized",
1291
+ "radicalises": "radicalizes",
1292
+ "radicalising": "radicalizing",
1293
+ "rancour": "rancor",
1294
+ "randomise": "randomize",
1295
+ "randomised": "randomized",
1296
+ "randomises": "randomizes",
1297
+ "randomising": "randomizing",
1298
+ "rationalisation": "rationalization",
1299
+ "rationalisations": "rationalizations",
1300
+ "rationalise": "rationalize",
1301
+ "rationalised": "rationalized",
1302
+ "rationalises": "rationalizes",
1303
+ "rationalising": "rationalizing",
1304
+ "ravelled": "raveled",
1305
+ "ravelling": "raveling",
1306
+ "realisable": "realizable",
1307
+ "realisation": "realization",
1308
+ "realisations": "realizations",
1309
+ "realise": "realize",
1310
+ "realised": "realized",
1311
+ "realises": "realizes",
1312
+ "realising": "realizing",
1313
+ "recognisable": "recognizable",
1314
+ "recognisably": "recognizably",
1315
+ "recognisance": "recognizance",
1316
+ "recognise": "recognize",
1317
+ "recognised": "recognized",
1318
+ "recognises": "recognizes",
1319
+ "recognising": "recognizing",
1320
+ "reconnoitre": "reconnoiter",
1321
+ "reconnoitred": "reconnoitered",
1322
+ "reconnoitres": "reconnoiters",
1323
+ "reconnoitring": "reconnoitering",
1324
+ "refuelled": "refueled",
1325
+ "refuelling": "refueling",
1326
+ "regularisation": "regularization",
1327
+ "regularise": "regularize",
1328
+ "regularised": "regularized",
1329
+ "regularises": "regularizes",
1330
+ "regularising": "regularizing",
1331
+ "remodelled": "remodeled",
1332
+ "remodelling": "remodeling",
1333
+ "remould": "remold",
1334
+ "remoulded": "remolded",
1335
+ "remoulding": "remolding",
1336
+ "remoulds": "remolds",
1337
+ "reorganisation": "reorganization",
1338
+ "reorganisations": "reorganizations",
1339
+ "reorganise": "reorganize",
1340
+ "reorganised": "reorganized",
1341
+ "reorganises": "reorganizes",
1342
+ "reorganising": "reorganizing",
1343
+ "revelled": "reveled",
1344
+ "reveller": "reveler",
1345
+ "revellers": "revelers",
1346
+ "revelling": "reveling",
1347
+ "revitalise": "revitalize",
1348
+ "revitalised": "revitalized",
1349
+ "revitalises": "revitalizes",
1350
+ "revitalising": "revitalizing",
1351
+ "revolutionise": "revolutionize",
1352
+ "revolutionised": "revolutionized",
1353
+ "revolutionises": "revolutionizes",
1354
+ "revolutionising": "revolutionizing",
1355
+ "rhapsodise": "rhapsodize",
1356
+ "rhapsodised": "rhapsodized",
1357
+ "rhapsodises": "rhapsodizes",
1358
+ "rhapsodising": "rhapsodizing",
1359
+ "rigour": "rigor",
1360
+ "rigours": "rigors",
1361
+ "ritualised": "ritualized",
1362
+ "rivalled": "rivaled",
1363
+ "rivalling": "rivaling",
1364
+ "romanticise": "romanticize",
1365
+ "romanticised": "romanticized",
1366
+ "romanticises": "romanticizes",
1367
+ "romanticising": "romanticizing",
1368
+ "rumour": "rumor",
1369
+ "rumoured": "rumored",
1370
+ "rumours": "rumors",
1371
+ "sabre": "saber",
1372
+ "sabres": "sabers",
1373
+ "saltpetre": "saltpeter",
1374
+ "sanitise": "sanitize",
1375
+ "sanitised": "sanitized",
1376
+ "sanitises": "sanitizes",
1377
+ "sanitising": "sanitizing",
1378
+ "satirise": "satirize",
1379
+ "satirised": "satirized",
1380
+ "satirises": "satirizes",
1381
+ "satirising": "satirizing",
1382
+ "saviour": "savior",
1383
+ "saviours": "saviors",
1384
+ "savour": "savor",
1385
+ "savoured": "savored",
1386
+ "savouries": "savories",
1387
+ "savouring": "savoring",
1388
+ "savours": "savors",
1389
+ "savoury": "savory",
1390
+ "scandalise": "scandalize",
1391
+ "scandalised": "scandalized",
1392
+ "scandalises": "scandalizes",
1393
+ "scandalising": "scandalizing",
1394
+ "sceptic": "skeptic",
1395
+ "sceptical": "skeptical",
1396
+ "sceptically": "skeptically",
1397
+ "scepticism": "skepticism",
1398
+ "sceptics": "skeptics",
1399
+ "sceptre": "scepter",
1400
+ "sceptres": "scepters",
1401
+ "scrutinise": "scrutinize",
1402
+ "scrutinised": "scrutinized",
1403
+ "scrutinises": "scrutinizes",
1404
+ "scrutinising": "scrutinizing",
1405
+ "secularisation": "secularization",
1406
+ "secularise": "secularize",
1407
+ "secularised": "secularized",
1408
+ "secularises": "secularizes",
1409
+ "secularising": "secularizing",
1410
+ "sensationalise": "sensationalize",
1411
+ "sensationalised": "sensationalized",
1412
+ "sensationalises": "sensationalizes",
1413
+ "sensationalising": "sensationalizing",
1414
+ "sensitise": "sensitize",
1415
+ "sensitised": "sensitized",
1416
+ "sensitises": "sensitizes",
1417
+ "sensitising": "sensitizing",
1418
+ "sentimentalise": "sentimentalize",
1419
+ "sentimentalised": "sentimentalized",
1420
+ "sentimentalises": "sentimentalizes",
1421
+ "sentimentalising": "sentimentalizing",
1422
+ "sepulchre": "sepulcher",
1423
+ "sepulchres": "sepulchers",
1424
+ "serialisation": "serialization",
1425
+ "serialisations": "serializations",
1426
+ "serialise": "serialize",
1427
+ "serialised": "serialized",
1428
+ "serialises": "serializes",
1429
+ "serialising": "serializing",
1430
+ "sermonise": "sermonize",
1431
+ "sermonised": "sermonized",
1432
+ "sermonises": "sermonizes",
1433
+ "sermonising": "sermonizing",
1434
+ "sheikh": "sheik",
1435
+ "shovelled": "shoveled",
1436
+ "shovelling": "shoveling",
1437
+ "shrivelled": "shriveled",
1438
+ "shrivelling": "shriveling",
1439
+ "signalise": "signalize",
1440
+ "signalised": "signalized",
1441
+ "signalises": "signalizes",
1442
+ "signalising": "signalizing",
1443
+ "signalled": "signaled",
1444
+ "signalling": "signaling",
1445
+ "smoulder": "smolder",
1446
+ "smouldered": "smoldered",
1447
+ "smouldering": "smoldering",
1448
+ "smoulders": "smolders",
1449
+ "snivelled": "sniveled",
1450
+ "snivelling": "sniveling",
1451
+ "snorkelled": "snorkeled",
1452
+ "snorkelling": "snorkeling",
1453
+ "snowplough": "snowplow",
1454
+ "snowploughs": "snowplow",
1455
+ "socialisation": "socialization",
1456
+ "socialise": "socialize",
1457
+ "socialised": "socialized",
1458
+ "socialises": "socializes",
1459
+ "socialising": "socializing",
1460
+ "sodomise": "sodomize",
1461
+ "sodomised": "sodomized",
1462
+ "sodomises": "sodomizes",
1463
+ "sodomising": "sodomizing",
1464
+ "solemnise": "solemnize",
1465
+ "solemnised": "solemnized",
1466
+ "solemnises": "solemnizes",
1467
+ "solemnising": "solemnizing",
1468
+ "sombre": "somber",
1469
+ "specialisation": "specialization",
1470
+ "specialisations": "specializations",
1471
+ "specialise": "specialize",
1472
+ "specialised": "specialized",
1473
+ "specialises": "specializes",
1474
+ "specialising": "specializing",
1475
+ "spectre": "specter",
1476
+ "spectres": "specters",
1477
+ "spiralled": "spiraled",
1478
+ "spiralling": "spiraling",
1479
+ "splendour": "splendor",
1480
+ "splendours": "splendors",
1481
+ "squirrelled": "squirreled",
1482
+ "squirrelling": "squirreling",
1483
+ "stabilisation": "stabilization",
1484
+ "stabilise": "stabilize",
1485
+ "stabilised": "stabilized",
1486
+ "stabiliser": "stabilizer",
1487
+ "stabilisers": "stabilizers",
1488
+ "stabilises": "stabilizes",
1489
+ "stabilising": "stabilizing",
1490
+ "standardisation": "standardization",
1491
+ "standardise": "standardize",
1492
+ "standardised": "standardized",
1493
+ "standardises": "standardizes",
1494
+ "standardising": "standardizing",
1495
+ "stencilled": "stenciled",
1496
+ "stencilling": "stenciling",
1497
+ "sterilisation": "sterilization",
1498
+ "sterilisations": "sterilizations",
1499
+ "sterilise": "sterilize",
1500
+ "sterilised": "sterilized",
1501
+ "steriliser": "sterilizer",
1502
+ "sterilisers": "sterilizers",
1503
+ "sterilises": "sterilizes",
1504
+ "sterilising": "sterilizing",
1505
+ "stigmatisation": "stigmatization",
1506
+ "stigmatise": "stigmatize",
1507
+ "stigmatised": "stigmatized",
1508
+ "stigmatises": "stigmatizes",
1509
+ "stigmatising": "stigmatizing",
1510
+ "storey": "story",
1511
+ "storeys": "stories",
1512
+ "subsidisation": "subsidization",
1513
+ "subsidise": "subsidize",
1514
+ "subsidised": "subsidized",
1515
+ "subsidiser": "subsidizer",
1516
+ "subsidisers": "subsidizers",
1517
+ "subsidises": "subsidizes",
1518
+ "subsidising": "subsidizing",
1519
+ "succour": "succor",
1520
+ "succoured": "succored",
1521
+ "succouring": "succoring",
1522
+ "succours": "succors",
1523
+ "sulphate": "sulfate",
1524
+ "sulphates": "sulfates",
1525
+ "sulphide": "sulfide",
1526
+ "sulphides": "sulfides",
1527
+ "sulphur": "sulfur",
1528
+ "sulphurous": "sulfurous",
1529
+ "summarise": "summarize",
1530
+ "summarised": "summarized",
1531
+ "summarises": "summarizes",
1532
+ "summarising": "summarizing",
1533
+ "swivelled": "swiveled",
1534
+ "swivelling": "swiveling",
1535
+ "symbolise": "symbolize",
1536
+ "symbolised": "symbolized",
1537
+ "symbolises": "symbolizes",
1538
+ "symbolising": "symbolizing",
1539
+ "sympathise": "sympathize",
1540
+ "sympathised": "sympathized",
1541
+ "sympathiser": "sympathizer",
1542
+ "sympathisers": "sympathizers",
1543
+ "sympathises": "sympathizes",
1544
+ "sympathising": "sympathizing",
1545
+ "synchronisation": "synchronization",
1546
+ "synchronise": "synchronize",
1547
+ "synchronised": "synchronized",
1548
+ "synchronises": "synchronizes",
1549
+ "synchronising": "synchronizing",
1550
+ "synthesise": "synthesize",
1551
+ "synthesised": "synthesized",
1552
+ "synthesiser": "synthesizer",
1553
+ "synthesisers": "synthesizers",
1554
+ "synthesises": "synthesizes",
1555
+ "synthesising": "synthesizing",
1556
+ "syphon": "siphon",
1557
+ "syphoned": "siphoned",
1558
+ "syphoning": "siphoning",
1559
+ "syphons": "siphons",
1560
+ "systematisation": "systematization",
1561
+ "systematise": "systematize",
1562
+ "systematised": "systematized",
1563
+ "systematises": "systematizes",
1564
+ "systematising": "systematizing",
1565
+ "tantalise": "tantalize",
1566
+ "tantalised": "tantalized",
1567
+ "tantalises": "tantalizes",
1568
+ "tantalising": "tantalizing",
1569
+ "tantalisingly": "tantalizingly",
1570
+ "tasselled": "tasseled",
1571
+ "technicolour": "technicolor",
1572
+ "temporise": "temporize",
1573
+ "temporised": "temporized",
1574
+ "temporises": "temporizes",
1575
+ "temporising": "temporizing",
1576
+ "tenderise": "tenderize",
1577
+ "tenderised": "tenderized",
1578
+ "tenderises": "tenderizes",
1579
+ "tenderising": "tenderizing",
1580
+ "terrorise": "terrorize",
1581
+ "terrorised": "terrorized",
1582
+ "terrorises": "terrorizes",
1583
+ "terrorising": "terrorizing",
1584
+ "theatre": "theater",
1585
+ "theatregoer": "theatergoer",
1586
+ "theatregoers": "theatergoers",
1587
+ "theatres": "theaters",
1588
+ "theorise": "theorize",
1589
+ "theorised": "theorized",
1590
+ "theorises": "theorizes",
1591
+ "theorising": "theorizing",
1592
+ "tonne": "ton",
1593
+ "tonnes": "tons",
1594
+ "towelled": "toweled",
1595
+ "towelling": "toweling",
1596
+ "toxaemia": "toxemia",
1597
+ "tranquillise": "tranquilize",
1598
+ "tranquillised": "tranquilized",
1599
+ "tranquilliser": "tranquilizer",
1600
+ "tranquillisers": "tranquilizers",
1601
+ "tranquillises": "tranquilizes",
1602
+ "tranquillising": "tranquilizing",
1603
+ "tranquillity": "tranquility",
1604
+ "tranquillize": "tranquilize",
1605
+ "tranquillized": "tranquilized",
1606
+ "tranquillizer": "tranquilizer",
1607
+ "tranquillizers": "tranquilizers",
1608
+ "tranquillizes": "tranquilizes",
1609
+ "tranquillizing": "tranquilizing",
1610
+ "tranquilly": "tranquility",
1611
+ "transistorised": "transistorized",
1612
+ "traumatise": "traumatize",
1613
+ "traumatised": "traumatized",
1614
+ "traumatises": "traumatizes",
1615
+ "traumatising": "traumatizing",
1616
+ "travelled": "traveled",
1617
+ "traveller": "traveler",
1618
+ "travellers": "travelers",
1619
+ "travelling": "traveling",
1620
+ "travelog": "travelogue",
1621
+ "travelogs": "travelogues",
1622
+ "trialled": "trialed",
1623
+ "trialling": "trialing",
1624
+ "tricolour": "tricolor",
1625
+ "tricolours": "tricolors",
1626
+ "trivialise": "trivialize",
1627
+ "trivialised": "trivialized",
1628
+ "trivialises": "trivializes",
1629
+ "trivialising": "trivializing",
1630
+ "tumour": "tumor",
1631
+ "tumours": "tumors",
1632
+ "tunnelled": "tunneled",
1633
+ "tunnelling": "tunneling",
1634
+ "tyrannise": "tyrannize",
1635
+ "tyrannised": "tyrannized",
1636
+ "tyrannises": "tyrannizes",
1637
+ "tyrannising": "tyrannizing",
1638
+ "tyre": "tire",
1639
+ "tyres": "tires",
1640
+ "unauthorised": "unauthorized",
1641
+ "uncivilised": "uncivilized",
1642
+ "underutilised": "underutilized",
1643
+ "unequalled": "unequaled",
1644
+ "unfavourable": "unfavorable",
1645
+ "unfavourably": "unfavorably",
1646
+ "unionisation": "unionization",
1647
+ "unionise": "unionize",
1648
+ "unionised": "unionized",
1649
+ "unionises": "unionizes",
1650
+ "unionising": "unionizing",
1651
+ "unorganised": "unorganized",
1652
+ "unravelled": "unraveled",
1653
+ "unravelling": "unraveling",
1654
+ "unrecognisable": "unrecognizable",
1655
+ "unrecognised": "unrecognized",
1656
+ "unrivalled": "unrivaled",
1657
+ "unsavoury": "unsavory",
1658
+ "untrammelled": "untrammeled",
1659
+ "urbanisation": "urbanization",
1660
+ "urbanise": "urbanize",
1661
+ "urbanised": "urbanized",
1662
+ "urbanises": "urbanizes",
1663
+ "urbanising": "urbanizing",
1664
+ "utilisable": "utilizable",
1665
+ "utilisation": "utilization",
1666
+ "utilise": "utilize",
1667
+ "utilised": "utilized",
1668
+ "utilises": "utilizes",
1669
+ "utilising": "utilizing",
1670
+ "valour": "valor",
1671
+ "vandalise": "vandalize",
1672
+ "vandalised": "vandalized",
1673
+ "vandalises": "vandalizes",
1674
+ "vandalising": "vandalizing",
1675
+ "vaporisation": "vaporization",
1676
+ "vaporise": "vaporize",
1677
+ "vaporised": "vaporized",
1678
+ "vaporises": "vaporizes",
1679
+ "vaporising": "vaporizing",
1680
+ "vapour": "vapor",
1681
+ "vapours": "vapors",
1682
+ "verbalise": "verbalize",
1683
+ "verbalised": "verbalized",
1684
+ "verbalises": "verbalizes",
1685
+ "verbalising": "verbalizing",
1686
+ "victimisation": "victimization",
1687
+ "victimise": "victimize",
1688
+ "victimised": "victimized",
1689
+ "victimises": "victimizes",
1690
+ "victimising": "victimizing",
1691
+ "videodisc": "videodisk",
1692
+ "videodiscs": "videodisks",
1693
+ "vigour": "vigor",
1694
+ "visualisation": "visualization",
1695
+ "visualisations": "visualizations",
1696
+ "visualise": "visualize",
1697
+ "visualised": "visualized",
1698
+ "visualises": "visualizes",
1699
+ "visualising": "visualizing",
1700
+ "vocalisation": "vocalization",
1701
+ "vocalisations": "vocalizations",
1702
+ "vocalise": "vocalize",
1703
+ "vocalised": "vocalized",
1704
+ "vocalises": "vocalizes",
1705
+ "vocalising": "vocalizing",
1706
+ "vulcanised": "vulcanized",
1707
+ "vulgarisation": "vulgarization",
1708
+ "vulgarise": "vulgarize",
1709
+ "vulgarised": "vulgarized",
1710
+ "vulgarises": "vulgarizes",
1711
+ "vulgarising": "vulgarizing",
1712
+ "waggon": "wagon",
1713
+ "waggons": "wagons",
1714
+ "watercolour": "watercolor",
1715
+ "watercolours": "watercolors",
1716
+ "weaselled": "weaseled",
1717
+ "weaselling": "weaseling",
1718
+ "westernisation": "westernization",
1719
+ "westernise": "westernize",
1720
+ "westernised": "westernized",
1721
+ "westernises": "westernizes",
1722
+ "westernising": "westernizing",
1723
+ "womanise": "womanize",
1724
+ "womanised": "womanized",
1725
+ "womaniser": "womanizer",
1726
+ "womanisers": "womanizers",
1727
+ "womanises": "womanizes",
1728
+ "womanising": "womanizing",
1729
+ "woollen": "woolen",
1730
+ "woollens": "woolens",
1731
+ "woollies": "woolies",
1732
+ "woolly": "wooly",
1733
+ "worshipped": "worshiped",
1734
+ "worshipper": "worshiper",
1735
+ "worshipping": "worshiping",
1736
+ "yodelled": "yodeled",
1737
+ "yodelling": "yodeling",
1738
+ "yoghourt": "yogurt",
1739
+ "yoghourts": "yogurts",
1740
+ "yoghurt": "yogurt",
1741
+ "yoghurts": "yogurts"
1742
+ }
onnx/preprocessor_config.json ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "chunk_length": 30,
3
+ "feature_extractor_type": "WhisperFeatureExtractor",
4
+ "feature_size": 80,
5
+ "hop_length": 160,
6
+ "n_fft": 400,
7
+ "n_samples": 480000,
8
+ "nb_max_frames": 3000,
9
+ "padding_side": "right",
10
+ "padding_value": 0.0,
11
+ "processor_class": "WhisperProcessor",
12
+ "return_attention_mask": false,
13
+ "sampling_rate": 16000
14
+ }
onnx/special_tokens_map.json ADDED
@@ -0,0 +1,139 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|endoftext|>",
4
+ "<|startoftranscript|>",
5
+ "<|en|>",
6
+ "<|zh|>",
7
+ "<|de|>",
8
+ "<|es|>",
9
+ "<|ru|>",
10
+ "<|ko|>",
11
+ "<|fr|>",
12
+ "<|ja|>",
13
+ "<|pt|>",
14
+ "<|tr|>",
15
+ "<|pl|>",
16
+ "<|ca|>",
17
+ "<|nl|>",
18
+ "<|ar|>",
19
+ "<|sv|>",
20
+ "<|it|>",
21
+ "<|id|>",
22
+ "<|hi|>",
23
+ "<|fi|>",
24
+ "<|vi|>",
25
+ "<|he|>",
26
+ "<|uk|>",
27
+ "<|el|>",
28
+ "<|ms|>",
29
+ "<|cs|>",
30
+ "<|ro|>",
31
+ "<|da|>",
32
+ "<|hu|>",
33
+ "<|ta|>",
34
+ "<|no|>",
35
+ "<|th|>",
36
+ "<|ur|>",
37
+ "<|hr|>",
38
+ "<|bg|>",
39
+ "<|lt|>",
40
+ "<|la|>",
41
+ "<|mi|>",
42
+ "<|ml|>",
43
+ "<|cy|>",
44
+ "<|sk|>",
45
+ "<|te|>",
46
+ "<|fa|>",
47
+ "<|lv|>",
48
+ "<|bn|>",
49
+ "<|sr|>",
50
+ "<|az|>",
51
+ "<|sl|>",
52
+ "<|kn|>",
53
+ "<|et|>",
54
+ "<|mk|>",
55
+ "<|br|>",
56
+ "<|eu|>",
57
+ "<|is|>",
58
+ "<|hy|>",
59
+ "<|ne|>",
60
+ "<|mn|>",
61
+ "<|bs|>",
62
+ "<|kk|>",
63
+ "<|sq|>",
64
+ "<|sw|>",
65
+ "<|gl|>",
66
+ "<|mr|>",
67
+ "<|pa|>",
68
+ "<|si|>",
69
+ "<|km|>",
70
+ "<|sn|>",
71
+ "<|yo|>",
72
+ "<|so|>",
73
+ "<|af|>",
74
+ "<|oc|>",
75
+ "<|ka|>",
76
+ "<|be|>",
77
+ "<|tg|>",
78
+ "<|sd|>",
79
+ "<|gu|>",
80
+ "<|am|>",
81
+ "<|yi|>",
82
+ "<|lo|>",
83
+ "<|uz|>",
84
+ "<|fo|>",
85
+ "<|ht|>",
86
+ "<|ps|>",
87
+ "<|tk|>",
88
+ "<|nn|>",
89
+ "<|mt|>",
90
+ "<|sa|>",
91
+ "<|lb|>",
92
+ "<|my|>",
93
+ "<|bo|>",
94
+ "<|tl|>",
95
+ "<|mg|>",
96
+ "<|as|>",
97
+ "<|tt|>",
98
+ "<|haw|>",
99
+ "<|ln|>",
100
+ "<|ha|>",
101
+ "<|ba|>",
102
+ "<|jw|>",
103
+ "<|su|>",
104
+ "<|translate|>",
105
+ "<|transcribe|>",
106
+ "<|startoflm|>",
107
+ "<|startofprev|>",
108
+ "<|nocaptions|>",
109
+ "<|notimestamps|>"
110
+ ],
111
+ "bos_token": {
112
+ "content": "<|endoftext|>",
113
+ "lstrip": false,
114
+ "normalized": true,
115
+ "rstrip": false,
116
+ "single_word": false
117
+ },
118
+ "eos_token": {
119
+ "content": "<|endoftext|>",
120
+ "lstrip": false,
121
+ "normalized": true,
122
+ "rstrip": false,
123
+ "single_word": false
124
+ },
125
+ "pad_token": {
126
+ "content": "<|endoftext|>",
127
+ "lstrip": false,
128
+ "normalized": true,
129
+ "rstrip": false,
130
+ "single_word": false
131
+ },
132
+ "unk_token": {
133
+ "content": "<|endoftext|>",
134
+ "lstrip": false,
135
+ "normalized": true,
136
+ "rstrip": false,
137
+ "single_word": false
138
+ }
139
+ }
onnx/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
onnx/tokenizer_config.json ADDED
The diff for this file is too large to render. See raw diff
 
onnx/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
pytorch_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:627c0ce68746607060530ea4c312459050c3227ba09b10480c5e8436006c961e
3
+ size 151096745
stats.md ADDED
@@ -0,0 +1,93 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ language:
3
+ - 'no'
4
+ license: apache-2.0
5
+ base_model: NbAiLab/nb-whisper-tiny-v0.7
6
+ tags:
7
+ - audio
8
+ - asr
9
+ - automatic-speech-recognition
10
+ - hf-asr-leaderboard
11
+ model-index:
12
+ - name: nb-whisper-tiny-v0.7-semantic
13
+ results: []
14
+ ---
15
+
16
+ <!-- This model card has been generated automatically according to the information Keras had access to. You should
17
+ probably proofread and complete it, then remove this comment. -->
18
+
19
+ # nb-whisper-tiny-v0.7-semantic
20
+
21
+ This model is a fine-tuned version of [NbAiLab/nb-whisper-tiny-v0.7](https://huggingface.co/NbAiLab/nb-whisper-tiny-v0.7) on the NbAiLab/ncc_speech_styling_v4 dataset.
22
+ It achieves the following results on the evaluation set:
23
+ - step: 249
24
+ - validation_nst_loss: 0.6579
25
+ - train_loss: 1.2508
26
+ - validation_nst_wer: 8.8029
27
+ - validation_nst_cer: 2.9662
28
+ - validation_nst_exact_wer: 9.6358
29
+ - validation_nst_exact_cer: 3.0880
30
+ - validation_clean_stortinget_no_loss: 0.7202
31
+ - validation_clean_stortinget_no_wer: 16.5324
32
+ - validation_clean_stortinget_no_cer: 9.1926
33
+ - validation_clean_stortinget_no_exact_wer: 20.6476
34
+ - validation_clean_stortinget_no_exact_cer: 9.9178
35
+
36
+ ## Model description
37
+
38
+ More information needed
39
+
40
+ ## Intended uses & limitations
41
+
42
+ More information needed
43
+
44
+ ## Training and evaluation data
45
+
46
+ More information needed
47
+
48
+ ## Training procedure
49
+
50
+ ### Training hyperparameters
51
+
52
+ The following hyperparameters were used during training:
53
+ - learning_rate: 2.5e-05
54
+ - lr_scheduler_type: linear
55
+ - per_device_train_batch_size: 32
56
+ - total_train_batch_size_per_node: 128
57
+ - total_train_batch_size: 1024
58
+ - total_optimization_steps: 250
59
+ - starting_optimization_step: None
60
+ - finishing_optimization_step: 250
61
+ - num_train_dataset_workers: 32
62
+ - num_hosts: 8
63
+ - total_num_training_examples: 256,000
64
+ - steps_per_epoch: _To be computed after first epoch_
65
+ - num_beams: None
66
+ - weight_decay: 0.01
67
+ - adam_beta1: 0.9
68
+ - adam_beta2: 0.98
69
+ - adam_epsilon: 0.00015
70
+ - dropout: True
71
+ - bpe_dropout_probability: 0.2
72
+ - activation_dropout_probability: 0.1
73
+
74
+ ### Training results
75
+
76
+ | step | validation_nst_loss | train_loss | validation_nst_wer | validation_nst_cer | validation_nst_exact_wer | validation_nst_exact_cer | validation_clean_stortinget_no_loss | validation_clean_stortinget_no_wer | validation_clean_stortinget_no_cer | validation_clean_stortinget_no_exact_wer | validation_clean_stortinget_no_exact_cer |
77
+ |:----:|:-------------------:|:----------:|:------------------:|:------------------:|:------------------------:|:------------------------:|:-----------------------------------:|:----------------------------------:|:----------------------------------:|:----------------------------------------:|:----------------------------------------:|
78
+ | 0 | 0.5155 | 1.4782 | 7.9155 | 2.5430 | 8.7103 | 2.6640 | 0.7153 | 15.8148 | 8.6090 | 19.7201 | 9.3061 |
79
+ | 40 | 0.5328 | 1.3581 | 8.6232 | 2.8926 | 9.6031 | 3.0477 | 0.7058 | 17.0843 | 9.6747 | 21.3213 | 10.4075 |
80
+ | 80 | 0.6321 | 1.1988 | 8.8464 | 3.1266 | 9.7447 | 3.2629 | 0.7131 | 16.8712 | 9.3548 | 20.9062 | 10.0570 |
81
+ | 120 | 0.6456 | 1.1956 | 8.7757 | 3.0306 | 9.6630 | 3.1585 | 0.7165 | 16.7243 | 9.2521 | 20.8113 | 9.9704 |
82
+ | 160 | 0.6455 | 1.2386 | 8.7648 | 2.9784 | 9.6195 | 3.1081 | 0.7188 | 16.7030 | 9.2259 | 20.8967 | 9.9658 |
83
+ | 200 | 0.6576 | 1.1753 | 8.6777 | 2.9336 | 9.4888 | 3.0559 | 0.7202 | 16.5917 | 9.1859 | 20.7188 | 9.9205 |
84
+ | 240 | 0.6577 | 1.1923 | 8.9226 | 2.9923 | 9.7338 | 3.1100 | 0.7214 | 16.6272 | 9.2176 | 20.7211 | 9.9396 |
85
+ | 249 | 0.6579 | 1.2508 | 8.8029 | 2.9662 | 9.6358 | 3.0880 |
86
+ | 249 | 0.7202 | 1.2508 | 16.5324 | 9.1926 | 20.6476 | 9.9178 |
87
+
88
+
89
+ ### Framework versions
90
+
91
+ - Transformers 4.34.1
92
+ - Datasets 2.15.0
93
+ - Tokenizers 0.14.1
tf_model.h5 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:71af659788f9b402c9f5d7cf1c1039dbd0c2467791b5ce8a8b332301df42f01f
3
+ size 151253960
update_template.py ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import json
2
+ import requests
3
+
4
+ def download_template(url):
5
+ response = requests.get(url)
6
+ response.raise_for_status()
7
+ return response.text
8
+
9
+ def replace_in_file(template, replacements):
10
+ for placeholder, replacement in replacements.items():
11
+ template = template.replace(placeholder, replacement)
12
+ return template
13
+
14
+ def main():
15
+ with open('model_def.json', 'r') as file:
16
+ model_def = json.load(file)
17
+
18
+ template_url = model_def["template_url"]
19
+ template_content = download_template(template_url)
20
+
21
+ output_content = replace_in_file(template_content, model_def["replacements"])
22
+ output_filename = 'README.md'
23
+
24
+ with open(output_filename, 'w') as output_file:
25
+ output_file.write(output_content)
26
+ print(f'Processed {output_filename}')
27
+
28
+ if __name__ == "__main__":
29
+ main()