wehub-resource-sync
54 lines
1.4 KiB
Markdown
54 lines
1.4 KiB
Markdown
---
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jupytext:
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formats: ipynb,md:myst
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text_representation:
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extension: .md
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format_name: myst
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format_version: '0.8'
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jupytext_version: 1.4.2
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kernelspec:
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display_name: Python 3
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language: python
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name: python3
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---
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# mlm
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Masked Language Model (MLM) predicts words that were originally hidden intentionally in a sentence.
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To perform such prediction, first load a pre-trained MLM (e.g., `bert-base-chinese`):
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````{margin} Batching is Faster
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```{hint}
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Predict multiple sentences in batch mode for faster speed!
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```
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````
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````{margin} Multilingual Support
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```{note}
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HanLP always support multilingual. Feel free to use a multilingual model listed [here](https://huggingface.co/models?pipeline_tag=fill-mask&sort=downloads).
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```
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````
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```{code-cell} ipython3
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:tags: [output_scroll]
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from hanlp.components.lm.mlm import MaskedLanguageModel
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mlm = MaskedLanguageModel()
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mlm.load('bert-base-chinese')
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```
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Represent blanks (masked tokens) with `[MASK]` and let MLM fills them:
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```{code-cell} ipython3
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:tags: [output_scroll]
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mlm('生活的真谛是[MASK]。')
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```
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Batching is always faster:
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```{code-cell} ipython3
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:tags: [output_scroll]
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mlm(['生活的真谛是[MASK]。', '巴黎是[MASK][MASK]的首都。'])
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```
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All the pre-trained MLM models and their details are listed in the [docs](https://huggingface.co/models?pipeline_tag=fill-mask&sort=downloads) of Hugging Face 🤗 Transformers. |