KoichiYasuoka commited on
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initial release

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README.md CHANGED
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- ---
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- license: cc-by-sa-4.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ language:
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+ - "uk"
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+ tags:
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+ - "ukrainian"
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+ - "token-classification"
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+ - "pos"
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+ - "ubertext"
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+ - "dependency-parsing"
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+ datasets:
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+ - "universal_dependencies"
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+ license: "cc-by-sa-4.0"
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+ pipeline_tag: "token-classification"
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+ ---
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+
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+ # roberta-base-ukrainian-upos
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+
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+ ## Model Description
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+
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+ This is a RoBERTa model pre-trained on Thai Wikipedia texts for POS-tagging and dependency-parsing, derived from [roberta-base-ukrainian](https://huggingface.co/KoichiYasuoka/roberta-base-ukrainian). Every word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech).
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+
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+ ## How to Use
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+
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+ ```py
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+ import torch
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+ from transformers import AutoTokenizer,AutoModelForTokenClassification
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+ tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-base-ukrainian-upos")
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+ model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/roberta-base-ukrainian-upos")
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+ ```
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+
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+ or
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+
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+ ```
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+ import esupar
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+ nlp=esupar.load("KoichiYasuoka/roberta-base-ukrainian-upos")
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+ ```
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+
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+ ## See Also
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+
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+ [esupar](https://github.com/KoichiYasuoka/esupar): Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa models
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+
config.json ADDED
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+ {
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+ "architectures": [
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+ "RobertaForTokenClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "bos_token_id": 0,
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+ "classifier_dropout": null,
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+ "eos_token_id": 2,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "ADJ",
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+ "1": "ADP",
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+ "2": "ADV",
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+ "3": "AUX",
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+ "4": "B-ADJ",
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+ "5": "B-ADP",
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+ "6": "B-ADV",
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+ "7": "B-AUX",
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+ "8": "B-CCONJ",
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+ "9": "B-DET",
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+ "10": "B-INTJ",
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+ "11": "B-NOUN",
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+ "12": "B-NOUN+NUM",
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+ "13": "B-NUM",
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+ "14": "B-NUM+NOUN",
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+ "15": "B-PART",
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+ "16": "B-PRON",
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+ "17": "B-PROPN",
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+ "18": "B-PUNCT",
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+ "19": "B-SCONJ",
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+ "20": "B-SYM",
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+ "21": "B-VERB",
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+ "22": "B-VERB+ADV",
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+ "23": "B-VERB+PRON",
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+ "24": "B-X",
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+ "25": "CCONJ",
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+ "26": "DET",
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+ "27": "I-ADJ",
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+ "28": "I-ADP",
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+ "29": "I-ADV",
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+ "30": "I-AUX",
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+ "31": "I-CCONJ",
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+ "32": "I-DET",
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+ "33": "I-INTJ",
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+ "34": "I-NOUN",
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+ "35": "I-NOUN+NUM",
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+ "36": "I-NUM",
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+ "37": "I-NUM+NOUN",
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+ "38": "I-PART",
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+ "39": "I-PRON",
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+ "40": "I-PROPN",
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+ "41": "I-PUNCT",
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+ "42": "I-SCONJ",
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+ "43": "I-SYM",
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+ "44": "I-VERB",
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+ "45": "I-VERB+ADV",
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+ "46": "I-VERB+PRON",
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+ "47": "I-X",
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+ "48": "INTJ",
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+ "49": "NOUN",
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+ "50": "NOUN+NUM",
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+ "51": "NUM",
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+ "52": "NUM+NOUN",
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+ "53": "PART",
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+ "54": "PRON",
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+ "55": "PROPN",
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+ "56": "PUNCT",
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+ "57": "SCONJ",
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+ "58": "SYM",
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+ "59": "VERB",
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+ "60": "VERB+ADV",
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+ "61": "VERB+PRON",
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+ "62": "X"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "ADJ": 0,
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+ "ADP": 1,
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+ "ADV": 2,
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+ "AUX": 3,
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+ "B-ADJ": 4,
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+ "B-ADP": 5,
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+ "B-ADV": 6,
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+ "B-AUX": 7,
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+ "B-CCONJ": 8,
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+ "B-DET": 9,
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+ "B-INTJ": 10,
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+ "B-NOUN": 11,
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+ "B-NOUN+NUM": 12,
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+ "B-NUM": 13,
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+ "B-NUM+NOUN": 14,
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+ "B-PART": 15,
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+ "B-PRON": 16,
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+ "B-PROPN": 17,
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+ "B-PUNCT": 18,
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+ "B-SCONJ": 19,
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+ "B-SYM": 20,
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+ "B-VERB": 21,
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+ "B-VERB+ADV": 22,
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+ "B-VERB+PRON": 23,
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+ "B-X": 24,
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+ "CCONJ": 25,
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+ "DET": 26,
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+ "I-ADJ": 27,
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+ "I-ADP": 28,
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+ "I-ADV": 29,
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+ "I-AUX": 30,
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+ "I-CCONJ": 31,
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+ "I-DET": 32,
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+ "I-VERB": 44,
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+ "I-VERB+PRON": 46,
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+ "VERB": 59,
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+ "VERB+ADV": 60,
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+ "VERB+PRON": 61,
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+ "X": 62
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "roberta",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 1,
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+ "position_embedding_type": "absolute",
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+ "task_specific_params": {
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+ "upos_multiword": {
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+ "NUM+NOUN": {
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+ "\u043f\u0456\u0432'\u044f\u0440\u0434\u0430": [
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+ "\u043f\u0456\u0432",
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+ "\u043f\u0456\u0432",
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+ "\u044f\u0449\u0438\u043a\u0430"
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+ ]
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+ },
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+ "VERB+ADV": {
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+ "\u043d\u0456\u0434\u0435": [
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+ "\u043d\u0435\u043c\u0430\u0454",
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+ "\u0434\u0435"
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+ "\u043d\u0456\u044f\u043a": [
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+ "\u043d\u0435\u043c\u0430\u0454",
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+ "\u044f\u043a"
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+ "VERB+PRON": {
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+ "\u043d\u0456\u043a\u0438\u043c": [
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+ }
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+ }
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+ },
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+ "tokenizer_class": "BertTokenizerFast",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.14.1",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 30000
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+ }
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