HRBert-mini
Browse files- README.md +45 -0
- config.json +27 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +1 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
README.md
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---
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language: ["ru", "en", "be", "bg", "uk", "ro", "kz", "tg", "tat", "sv", "sl", "sr", "uz", "es", "fi"]
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tags:
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- russian
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- fill-mask
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- pretraining
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- embeddings
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- masked-lm
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license: mit
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widget:
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- text: "[MASK] категории С"
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---
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This is a distilled Herbert model for an mlm task.
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Sentence embeddings can be produced as follows:
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```python
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# pip install transformers
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from transformers import pipeline
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fill_mask = pipeline(
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"fill-mask",
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model='RabotaRu/HRBert-mini',
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tokenizer='RabotaRu/HRBert-mini'
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)
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fill_mask('требуется <mask> менеджер')
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```
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config.json
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{
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"architectures": [
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"RobertaForMaskedLM"
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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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"emb_size": 384,
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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": 384,
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"initializer_range": 0.02,
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"intermediate_size": 512,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 514,
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"model_type": "roberta",
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"num_attention_heads": 12,
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"num_hidden_layers": 3,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.11.3",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 200001
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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:cb723ea01cb97ca3041bd5a345502a97adf43f1065b0babd687007e1b80fa4e4
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size 321258804
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special_tokens_map.json
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{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>", "cls_token": "<cls>", "mask_token": "<mask>"}
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tokenizer.json
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tokenizer_config.json
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{"special_tokens_map_file": "./HRBert2/special_tokens_map.json", "name_or_path": "./HRBert2", "tokenizer_class": "PreTrainedTokenizerFast"}
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