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[DOC] Cite source of pretrained parameters for bert_12_768_12 (#915)
* Cite source of pretrained parameters for bert_12_768_12 * Add citation to modelzoo page * Fix links
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scripts/bert/index.rst

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@@ -57,6 +57,30 @@ where **bert_12_768_12** refers to the BERT BASE model, and **bert_24_1024_16**
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words, valid_len, segments = mx.nd.array([sample[0]]), mx.nd.array([sample[1]]), mx.nd.array([sample[2]]);
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seq_encoding, cls_encoding = model(words, segments, valid_len);
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The pretrained parameters for dataset_name
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'openwebtext_book_corpus_wiki_en_uncased' were obtained by running the GluonNLP
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BERT pre-training script on OpenWebText.
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The pretrained parameters for dataset_name 'scibert_scivocab_uncased',
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'scibert_scivocab_cased', 'scibert_basevocab_uncased', 'scibert_basevocab_cased'
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were obtained by converting the parameters published by "Beltagy, I., Cohan, A.,
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& Lo, K. (2019). Scibert: Pretrained contextualized embeddings for scientific
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text. arXiv preprint `arXiv:1903.10676 <https://arxiv.org/abs/1903.10676>`_."
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The pretrained parameters for dataset_name 'biobert_v1.0_pmc',
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'biobert_v1.0_pubmed', 'biobert_v1.0_pubmed_pmc', 'biobert_v1.1_pubmed' were
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obtained by converting the parameters published by "Lee, J., Yoon, W., Kim, S.,
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Kim, D., Kim, S., So, C. H., & Kang, J. (2019). Biobert: pre-trained biomedical
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language representation model for biomedical text mining. arXiv preprint
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`arXiv:1901.08746 <https://arxiv.org/abs/1901.08746>`_."
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The pretrained parameters for dataset_name 'clinicalbert' were obtained by
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converting the parameters published by "Huang, K., Altosaar, J., & Ranganath, R.
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(2019). ClinicalBERT: Modeling Clinical Notes and Predicting Hospital
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Readmission. arXiv preprint `arXiv:1904.05342
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<https://arxiv.org/abs/1904.05342>`_."
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Additionally, GluonNLP supports the "`RoBERTa <https://arxiv.org/abs/1907.11692>`_" model:
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+-----------------------------------------+-------------------+--------------------+

src/gluonnlp/model/bert.py

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@@ -747,7 +747,7 @@ def bert_12_768_12(dataset_name=None, vocab=None, pretrained=True, ctx=mx.cpu(),
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'openwebtext_book_corpus_wiki_en_uncased',
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'wiki_multilingual_uncased', 'wiki_multilingual_cased',
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'scibert_scivocab_uncased', 'scibert_scivocab_cased',
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'scibert_basevocab_uncased','scibert_basevocab_cased',
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'scibert_basevocab_uncased', 'scibert_basevocab_cased',
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'biobert_v1.0_pmc', 'biobert_v1.0_pubmed', 'biobert_v1.0_pubmed_pmc',
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'biobert_v1.1_pubmed',
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'clinicalbert'
@@ -789,6 +789,30 @@ def bert_12_768_12(dataset_name=None, vocab=None, pretrained=True, ctx=mx.cpu(),
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parameters will be left uninitialized. Otherwise AssertionError is
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raised.
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The pretrained parameters for dataset_name
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'openwebtext_book_corpus_wiki_en_uncased' were obtained by running the
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GluonNLP BERT pre-training script on OpenWebText.
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The pretrained parameters for dataset_name 'scibert_scivocab_uncased',
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'scibert_scivocab_cased', 'scibert_basevocab_uncased',
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'scibert_basevocab_cased' were obtained by converting the parameters
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published by "Beltagy, I., Cohan, A., & Lo, K. (2019). Scibert: Pretrained
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contextualized embeddings for scientific text. arXiv preprint
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arXiv:1903.10676."
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The pretrained parameters for dataset_name 'biobert_v1.0_pmc',
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'biobert_v1.0_pubmed', 'biobert_v1.0_pubmed_pmc', 'biobert_v1.1_pubmed'
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were obtained by converting the parameters published by "Lee, J., Yoon, W.,
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Kim, S., Kim, D., Kim, S., So, C. H., & Kang, J. (2019). Biobert:
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pre-trained biomedical language representation model for biomedical text
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mining. arXiv preprint arXiv:1901.08746."
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The pretrained parameters for dataset_name 'clinicalbert' were obtained by
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converting the parameters published by "Huang, K., Altosaar, J., &
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Ranganath, R. (2019). ClinicalBERT: Modeling Clinical Notes and Predicting
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Hospital Readmission. arXiv preprint arXiv:1904.05342."
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Returns
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-------
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BERTModel, gluonnlp.vocab.BERTVocab

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