Push model files with MedDRA thesaurus embeddings
Browse files- README.md +12 -0
- config.json +32 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +1 -0
- thesaurus_embeddings_meddra_origin.pt +3 -0
- tokenizer_config.json +1 -0
- vocab.txt +0 -0
README.md
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---
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language:
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- ru
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---
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# rubert-base-cased
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RuBERT \(Russian, cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\) was trained on the Russian part of Wikipedia and news data. We used this training data to build a vocabulary of Russian subtokens and took a multilingual version of BERT‑base as an initialization for RuBERT\[1\].
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08.11.2021: upload model with MLM and NSP heads
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\[1\]: Kuratov, Y., Arkhipov, M. \(2019\). Adaptation of Deep Bidirectional Multilingual Transformers for Russian Language. arXiv preprint [arXiv:1905.07213](https://arxiv.org/abs/1905.07213).
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config.json
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{
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"_name_or_path": "DeepPavlov/rubert-base-cased",
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"architectures": [
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"BertModel"
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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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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"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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"torch_dtype": "float32",
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"transformers_version": "4.15.0",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 119547
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:d0a0216856db094c274125b7f357d844d9657a3b30f78455f2143f869a26163c
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size 711495089
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special_tokens_map.json
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
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thesaurus_embeddings_meddra_origin.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:e1e70ce03cd01cb6582d79087fe85a6ff14263dbefdb18ab699b668028b650ed
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size 77037291
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tokenizer_config.json
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{"do_lower_case": false}
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vocab.txt
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