# mlwithme/BertWithPretrained

<https://repo.masters-masters.com/en/repos/mlwithme/BertWithPretrained>

[Home](https://repo.masters-masters.com/en) › [mlwithme](https://repo.masters-masters.com/en/owners/mlwithme) › [BertWithPretrained](https://repo.masters-masters.com/en/repos/mlwithme/BertWithPretrained)

mlwithme/BertWithPretrained has 602 stars on GitHub. Its RepoMasters card: Alpha tier. An implementation of the BERT model and its related downstream tasks…

| Field | Value |
| --- | --- |
| Owner | [mlwithme](https://repo.masters-masters.com/en/owners/mlwithme) |
| Stars | 602 |
| Forks | 108 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | None |
| Created | 2021 |
| Topics | bert, pytorch, nlp, swag, deep-learning, pretrained-models, question-answering, squad, text-classification |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [mlwithme/BertWithPretrained](https://github.com/mlwithme/BertWithPretrained) |

## Repository

An implementation of the BERT model and its related downstream tasks based on the PyTorch framework. @跟我学机器学习

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

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