Migrate model card from transformers-repo
Browse filesRead announcement at https://discuss.huggingface.co/t/announcement-all-model-cards-will-be-migrated-to-hf-co-model-repos/2755
Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/allegro/herbert-base-cased/README.md
README.md
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---
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language: pl
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tags:
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- herbert
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license: cc-by-sa-4.0
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---
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# HerBERT
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**[HerBERT](https://en.wikipedia.org/wiki/Zbigniew_Herbert)** is a BERT-based Language Model trained on Polish Corpora
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using MLM and SSO objectives with dynamic masking of whole words.
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Model training and experiments were conducted with [transformers](https://github.com/huggingface/transformers) in version 2.9.
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## Tokenizer
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The training dataset was tokenized into subwords using ``CharBPETokenizer`` a character level byte-pair encoding with
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a vocabulary size of 50k tokens. The tokenizer itself was trained with a [tokenizers](https://github.com/huggingface/tokenizers) library.
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We kindly encourage you to use the **Fast** version of tokenizer, namely ``HerbertTokenizerFast``.
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## HerBERT usage
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Example code:
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```python
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from transformers import AutoTokenizer, AutoModel
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tokenizer = AutoTokenizer.from_pretrained("allegro/herbert-base-cased")
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model = AutoModel.from_pretrained("allegro/herbert-base-cased")
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output = model(
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**tokenizer.batch_encode_plus(
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[
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(
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"A potem szedł środkiem drogi w kurzawie, bo zamiatał nogami, ślepy dziad prowadzony przez tłustego kundla na sznurku.",
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"A potem leciał od lasu chłopak z butelką, ale ten ujrzawszy księdza przy drodze okrążył go z dala i biegł na przełaj pól do karczmy."
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)
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],
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padding='longest',
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add_special_tokens=True,
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return_tensors='pt'
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)
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)
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```
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## License
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CC BY-SA 4.0
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## Authors
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Model was trained by **Allegro Machine Learning Research** team.
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You can contact us at: <a href="mailto:klejbenchmark@allegro.pl">klejbenchmark@allegro.pl</a>
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