coppercitylabs
commited on
Commit
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3047552
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Parent(s):
f772022
Add model
Browse files- LICENSE.md +20 -0
- README.md +62 -0
- config.json +24 -0
- pytorch_model.bin +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
- vocab.txt +0 -0
LICENSE.md
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Copyright 2021 CopperCityLabs
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Permission is hereby granted, free of charge, to any person obtaining a
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copy of this software and associated documentation files (the
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"Software"), to deal in the Software without restriction, including
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without limitation the rights to use, copy, modify, merge, publish,
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distribute, sublicense, and/or sell copies of the Software, and to
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permit persons to whom the Software is furnished to do so, subject to
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the following conditions:
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The above copyright notice and this permission notice shall be included
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in all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
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OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
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MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
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IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
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CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
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TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
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SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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README.md
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---
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language: uz (cyrl)
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tags:
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- uzbert
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- uzbek
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- bert
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license: MIT
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datasets:
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- webcrawl corpus (~142M words)
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---
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# UzBERT base model (uncased)
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Pretrained model on Uzbek language (Cyrillic script) using a masked
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language modeling and next sentence prediction objectives.
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### How to use
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You can use this model directly with a pipeline for masked language modeling:
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```python
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>>> from transformers import pipeline
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>>> unmasker = pipeline('fill-mask', model='coppercitylabs/uzbert-base-uncased')
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>>> unmasker("Алишер Навоий – улуғ ўзбек ва бошқа туркий халқларнинг [MASK], мутафаккири ва давлат арбоби бўлган.")
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[
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{
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'token_str': 'шоири',
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'token': 13587,
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'score': 0.7974384427070618,
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'sequence': 'алишер навоий – улуғ ўзбек ва бошқа туркий халқларнинг шоири, мутафаккир ##и ва давлат арбоби бўлган.'
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},
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{
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'token_str': 'олими',
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'token': 18500,
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'score': 0.09166576713323593,
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'sequence': 'алишер навоий – улуғ ўзбек ва бошқа туркий халқларнинг олими, мутафаккир ##и ва давлат арбоби бўлган.'
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},
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{
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'token_str': 'асосчиси',
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'token': 7469,
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'score': 0.02451123297214508,
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'sequence': 'алишер навоий – улуғ ўзбек ва бошқа туркий халқларнинг асосчиси, мутафаккир ##и ва давлат арбоби бўлган.'
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},
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{
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'token_str': 'ёзувчиси',
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'token': 22439,
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'score': 0.017601722851395607,
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'sequence': 'алишер навоий – улуғ ўзбек ва бошқа туркий халқларнинг ёзувчиси, мутафаккир ##и ва давлат арбоби бўлган.'
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},
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{
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'token_str': 'устози',
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'token': 11494,
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'score': 0.010115668177604675,
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'sequence': 'алишер навоий – улуғ ўзбек ва бошқа туркий халқларнинг устози, мутафаккир ##и ва давлат арбоби бўлган.'
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}
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]
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```
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## Training data
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UzBERT model was pretrained on ~625K news articles.
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config.json
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{
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"_name_or_path": "/home/b/uzl/src/bert/../..//out/bert/model-1/",
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"architectures": [
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"BertForMaskedLM"
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],
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"attention_probs_dropout_prob": 0.1,
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"gradient_checkpointing": false,
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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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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"transformers_version": "4.8.2",
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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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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:b3d626d7b124b38437492d465aaab46841d1a876427d4be2cac427e7060b9ac7
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size 436536363
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tokenizer.json
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tokenizer_config.json
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{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "special_tokens_map_file": null, "name_or_path": "/home/b/uzl/src/bert/../..//out/bert/", "tokenizer_class": "BertTokenizer"}
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vocab.txt
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