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KoichiYasuoka
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bert-base-russian-upos

Token Classification
Transformers
PyTorch
Russian
bert
russian
pos
dependency-parsing
Inference Endpoints
Model card Files Community
3
KoichiYasuoka commited on
Commit
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1 Parent(s): 860838f

initial release

Browse files
Files changed (8) hide show
  1. README.md +39 -3
  2. config.json +480 -0
  3. pytorch_model.bin +3 -0
  4. special_tokens_map.json +1 -0
  5. supar.model +3 -0
  6. tokenizer.json +0 -0
  7. tokenizer_config.json +1 -0
  8. vocab.txt +0 -0
README.md CHANGED
@@ -1,3 +1,39 @@
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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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+ - "ru"
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+ tags:
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+ - "russian"
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+ - "token-classification"
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+ - "pos"
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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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+ # bert-base-russian-upos
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+
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+ ## Model Description
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+
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+ This is a BERT model pre-trained with [UD_Russian](https://universaldependencies.org/en/) for POS-tagging and dependency-parsing, derived from [rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased). 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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+ from transformers import AutoTokenizer,AutoModelForTokenClassification
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+ tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/bert-base-russian-upos")
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+ model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/bert-base-russian-upos")
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+ ```
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+
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+ or
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+
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+ ```py
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+ import esupar
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+ nlp=esupar.load("KoichiYasuoka/bert-base-russian-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
@@ -0,0 +1,480 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "architectures": [
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+ "BertForTokenClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "classifier_dropout": null,
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+ "directionality": "bidi",
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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": "ADJ+NOUN",
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+ "2": "ADP",
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+ "3": "ADP+PRON",
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+ "4": "ADV",
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+ "5": "AUX",
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+ "6": "B-ADJ",
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+ "7": "B-ADJ+ADJ",
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+ "8": "B-ADJ+NOUN",
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+ "9": "B-ADJ+SCONJ",
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+ "10": "B-ADJ+VERB",
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+ "11": "B-ADP",
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+ "12": "B-ADP+DET",
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+ "13": "B-ADV",
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+ "14": "B-ADV+VERB",
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+ "15": "B-AUX",
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+ "16": "B-CCONJ",
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+ "17": "B-DET",
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+ "18": "B-INTJ",
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+ "19": "B-NOUN",
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+ "20": "B-NUM",
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+ "21": "B-NUM+ADJ",
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+ "22": "B-NUM+NOUN",
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+ "23": "B-PART",
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+ "24": "B-PART+PRON",
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+ "25": "B-PRON",
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+ "26": "B-PRON+PART",
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+ "27": "B-PROPN",
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+ "28": "B-PUNCT",
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+ "29": "B-SCONJ",
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+ "30": "B-SYM",
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+ "31": "B-SYM+NUM",
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+ "32": "B-VERB",
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+ "33": "B-VERB+ADV",
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+ "34": "B-VERB+PRON",
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+ "35": "B-X",
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+ "36": "B-X+X",
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+ "37": "CCONJ",
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+ "39": "I-ADJ",
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+ "40": "I-ADJ+ADJ",
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+ "41": "I-ADJ+NOUN",
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+ "42": "I-ADJ+SCONJ",
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+ "43": "I-ADJ+VERB",
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+ "44": "I-ADP",
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+ "45": "I-ADP+DET",
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+ "46": "I-ADV",
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+ "47": "I-ADV+VERB",
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+ "48": "I-AUX",
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+ "49": "I-CCONJ",
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+ "50": "I-DET",
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+ "51": "I-INTJ",
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+ "52": "I-NOUN",
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+ "53": "I-NUM",
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+ "54": "I-NUM+ADJ",
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+ "55": "I-NUM+NOUN",
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+ "56": "I-PART",
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+ "57": "I-PART+PRON",
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+ "58": "I-PRON",
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+ "59": "I-PRON+PART",
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+ "60": "I-PROPN",
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+ "61": "I-PUNCT",
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+ "62": "I-SCONJ",
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+ "63": "I-SYM",
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+ "64": "I-SYM+NUM",
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+ "65": "I-VERB",
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+ "66": "I-VERB+ADV",
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+ "67": "I-VERB+PRON",
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+ "68": "I-X",
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+ "70": "INTJ",
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+ "71": "NOUN",
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+ "72": "NUM",
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+ "74": "NUM+PROPN",
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+ "75": "NUM+SYM",
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+ "76": "PART",
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+ "77": "PRON",
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+ "78": "PROPN",
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+ "79": "PUNCT",
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+ "80": "SCONJ",
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+ "81": "SYM",
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+ "82": "SYM+NOUN",
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+ "83": "SYM+NUM",
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+ "84": "SYM+PROPN",
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+ "85": "VERB",
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+ "86": "VERB+ADV",
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+ "87": "VERB+PRON",
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+ "88": "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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+ "ADJ+NOUN": 1,
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+ "ADP": 2,
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+ "B-ADJ": 6,
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+ "B-ADJ+NOUN": 8,
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+ "DET": 38,
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+ "I-X": 68,
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+ "VERB": 85,
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+ "VERB+ADV": 86,
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+ "VERB+PRON": 87,
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+ "X": 88
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
197
+ "model_type": "bert",
198
+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "output_past": true,
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+ "pad_token_id": 0,
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+ "pooler_fc_size": 768,
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+ "pooler_num_attention_heads": 12,
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+ "pooler_num_fc_layers": 3,
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+ "pooler_size_per_head": 128,
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+ "pooler_type": "first_token_transform",
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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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+ "ADJ+ADJ": {
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+ "\u0432\u043e\u0435\u043d\u043d\u043e",
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+ "\u043c\u043e\u0440\u0441\u043a\u0430\u044f"
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+ ],
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+ "\u0432\u043e\u0435\u043d\u043d\u043e",
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+ "\u043c\u043e\u0440\u0441\u043a\u0443\u044e"
218
+ ],
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+ "\u0433\u043e\u0440\u043d\u043e",
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+ ],
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+ ],
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+ ],
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+ ]
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+ "\u043f\u0440\u043e\u0434\u0443\u043a\u0446\u0438\u0438"
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+ ]
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+ },
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+ ]
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+ "\u0441",
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+ ],
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+ "\u0441\u0442\u0435\u0445": [
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+ "\u0441",
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+ "\u0442\u0435\u0445"
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+ ]
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+ },
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+ "\u0441\u043d\u0438\u043c": [
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+ "\u0441",
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+ "\u043d\u0438\u043c"
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+ ]
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+ },
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+ "\u0442\u0440\u0435\u043d\u0438\u0440\u043e\u0432\u0430\u0442\u044c"
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+ ]
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+ },
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+ "NUM+NOUN": {
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+ "\u041f\u043e\u043b\u043b\u0438\u0442\u0440\u0430": [
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+ "\u041f\u043e\u043b",
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+ "\u043b\u0438\u0442\u0440\u0430"
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+ ],
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+ ],
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+ "\u043f\u043e\u043b",
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+ ],
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+ ],
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+ ],
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+ "\u043f\u043e\u043b",
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+ ],
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+ ],
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+ ],
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+ ],
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