Delete en_tokenizer
Browse files- en_tokenizer/README.md +0 -35
- en_tokenizer/config.json +0 -19
- en_tokenizer/pytorch_model.bin +0 -3
- en_tokenizer/special_tokens_map.json +0 -1
- en_tokenizer/tokenizer_config.json +0 -1
- en_tokenizer/vocab.txt +0 -0
en_tokenizer/README.md
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# ERNIE-2.0-large
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## Introduction
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ERNIE 2.0 is a continual pre-training framework proposed by Baidu in 2019,
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which builds and learns incrementally pre-training tasks through constant multi-task learning.
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Experimental results demonstrate that ERNIE 2.0 outperforms BERT and XLNet on 16 tasks including English tasks on GLUE benchmarks and several common tasks in Chinese.
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More detail: https://arxiv.org/abs/1907.12412
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## Released Model Info
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This released pytorch model is converted from the officially released PaddlePaddle ERNIE model and
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a series of experiments have been conducted to check the accuracy of the conversion.
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- Official PaddlePaddle ERNIE repo: https://github.com/PaddlePaddle/ERNIE
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- Pytorch Conversion repo: https://github.com/nghuyong/ERNIE-Pytorch
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## How to use
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```Python
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from transformers import AutoTokenizer, AutoModel
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tokenizer = AutoTokenizer.from_pretrained("nghuyong/ernie-2.0-large-en")
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model = AutoModel.from_pretrained("nghuyong/ernie-2.0-large-en")
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```
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## Citation
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```bibtex
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@article{sun2019ernie20,
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title={ERNIE 2.0: A Continual Pre-training Framework for Language Understanding},
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author={Sun, Yu and Wang, Shuohuan and Li, Yukun and Feng, Shikun and Tian, Hao and Wu, Hua and Wang, Haifeng},
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journal={arXiv preprint arXiv:1907.12412},
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year={2019}
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}
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```
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en_tokenizer/config.json
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{
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"attention_probs_dropout_prob": 0.1,
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"intermediate_size": 4096,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"initializer_range": 0.02,
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"max_position_embeddings": 512,
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"type_vocab_size": 4,
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"vocab_size": 30522,
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"pad_token_id": 0,
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"layer_norm_eps": 1e-05,
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"model_type": "ernie",
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"architectures": [
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"ErnieModel"
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]
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}
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en_tokenizer/pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:89ef99415c7bd5e585abdd19252a5e95ff42c361f4e6f8da823e989fd396395c
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size 1340701491
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en_tokenizer/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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en_tokenizer/tokenizer_config.json
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{"special_tokens_map_file": null, "full_tokenizer_file": null}
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en_tokenizer/vocab.txt
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