commit files to HF hub
Browse files- README.md +25 -0
- config.json +75 -0
- inference.py +10 -0
- openvino_model.bin +3 -0
- openvino_model.xml +0 -0
- preprocessor_config.json +10 -0
- special_tokens_map.json +6 -0
- tokenizer_config.json +48 -0
- vocab.json +34 -0
README.md
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---
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language:
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- en
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tags:
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- openvino
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---
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# facebook/hubert-large-ls960-ft
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This is the [facebook/hubert-large-ls960-ft](https://huggingface.co/facebook/hubert-large-ls960-ft) model converted to [OpenVINO](https://openvino.ai), for accelerated inference.
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An example of how to do inference on this model:
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```python
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from optimum.intel import OVModelForCTC
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from transformers import AutoProcessor, pipeline
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# model_id should be set to either a local directory or a model available on the HuggingFace hub.
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model_id = "helenai/facebook-hubert-large-ls960-ft-ov"
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feature_extractor = AutoProcessor.from_pretrained(model_id)
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model = OVModelForCTC.from_pretrained(model_id)
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pipe = pipeline("automatic-speech-recognition", model=model, feature_extractor=feature_extractor)
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result = pipe("hello world")
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print(result)
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```
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config.json
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{
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"_name_or_path": "facebook/hubert-large-ls960-ft",
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"activation_dropout": 0.1,
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"apply_spec_augment": true,
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"architectures": [
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"HubertForCTC"
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],
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"attention_dropout": 0.1,
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"bos_token_id": 1,
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"classifier_proj_size": 256,
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"conv_bias": true,
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"conv_dim": [
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512,
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512,
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512,
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512,
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512,
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512,
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512
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],
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"conv_kernel": [
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10,
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3,
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3,
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3,
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3,
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2,
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2
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],
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"conv_stride": [
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5,
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2,
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2,
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2,
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2,
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2,
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2
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],
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"ctc_loss_reduction": "sum",
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"ctc_zero_infinity": false,
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"diversity_loss_weight": 0.1,
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"do_stable_layer_norm": true,
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"eos_token_id": 2,
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"feat_extract_activation": "gelu",
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"feat_extract_dropout": 0.0,
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"feat_extract_norm": "layer",
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"feat_proj_dropout": 0.1,
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"feat_proj_layer_norm": true,
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"final_dropout": 0.1,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout": 0.1,
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"layer_norm_eps": 1e-05,
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"layerdrop": 0.1,
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"mask_feature_length": 10,
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"mask_feature_min_masks": 0,
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"mask_feature_prob": 0.0,
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"mask_time_length": 10,
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"mask_time_min_masks": 2,
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"mask_time_prob": 0.05,
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"model_type": "hubert",
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"num_attention_heads": 16,
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"num_conv_pos_embedding_groups": 16,
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"num_conv_pos_embeddings": 128,
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"num_feat_extract_layers": 7,
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"num_hidden_layers": 24,
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"pad_token_id": 0,
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"transformers_version": "4.39.3",
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"use_weighted_layer_sum": false,
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"vocab_size": 32
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}
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inference.py
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from optimum.intel import OVModelForCTC
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from transformers import AutoProcessor, pipeline
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# model_id should be set to either a local directory or a model available on the HuggingFace hub.
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model_id = "helenai/facebook-hubert-large-ls960-ft-ov"
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feature_extractor = AutoProcessor.from_pretrained(model_id)
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model = OVModelForCTC.from_pretrained(model_id)
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pipe = pipeline("automatic-speech-recognition", model=model, feature_extractor=feature_extractor)
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result = pipe("hello world")
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print(result)
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openvino_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:2f387de334e8045ba9803eaa75d29052345e5e2daa29eaf51c816c01ffb04203
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size 630933740
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openvino_model.xml
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The diff for this file is too large to render.
See raw diff
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preprocessor_config.json
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{
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"do_normalize": true,
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"feature_extractor_type": "Wav2Vec2FeatureExtractor",
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"feature_size": 1,
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"padding_side": "right",
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"padding_value": 0,
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"processor_class": "Wav2Vec2Processor",
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"return_attention_mask": true,
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"sampling_rate": 16000
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}
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special_tokens_map.json
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{
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"bos_token": "<s>",
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"eos_token": "</s>",
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"pad_token": "<pad>",
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"unk_token": "<unk>"
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}
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tokenizer_config.json
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{
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"added_tokens_decoder": {
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"0": {
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"content": "<pad>",
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"lstrip": true,
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"normalized": false,
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"rstrip": true,
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"single_word": false,
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"special": false
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},
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"1": {
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"content": "<s>",
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"lstrip": true,
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"normalized": false,
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"rstrip": true,
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"single_word": false,
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"special": false
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},
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"2": {
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"content": "</s>",
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"lstrip": true,
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"normalized": false,
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"rstrip": true,
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"single_word": false,
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"special": false
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},
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"3": {
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"content": "<unk>",
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"lstrip": true,
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"normalized": false,
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"rstrip": true,
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"single_word": false,
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"special": false
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}
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},
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"bos_token": "<s>",
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"clean_up_tokenization_spaces": true,
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"do_lower_case": false,
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"eos_token": "</s>",
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "<pad>",
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"processor_class": "Wav2Vec2Processor",
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"replace_word_delimiter_char": " ",
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"target_lang": null,
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"tokenizer_class": "Wav2Vec2CTCTokenizer",
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"unk_token": "<unk>",
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"word_delimiter_token": "|"
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}
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vocab.json
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{
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"'": 27,
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"</s>": 2,
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"<pad>": 0,
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"<s>": 1,
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"<unk>": 3,
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"A": 7,
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"B": 24,
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"C": 19,
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"D": 14,
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"E": 5,
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"F": 20,
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"G": 21,
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"H": 11,
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"I": 10,
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"J": 29,
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"K": 26,
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"L": 15,
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"M": 17,
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"N": 9,
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"O": 8,
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"P": 23,
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"Q": 30,
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"R": 13,
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"S": 12,
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"T": 6,
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"U": 16,
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"V": 25,
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"W": 18,
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"X": 28,
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"Y": 22,
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"Z": 31,
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"|": 4
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}
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