# mim-solutions/bert\_for\_longer\_texts

<https://repo.masters-masters.com/en/repos/mim-solutions/bert_for_longer_texts>

[Home](https://repo.masters-masters.com/en) › [mim-solutions](https://repo.masters-masters.com/en/owners/mim-solutions) › [bert\_for\_longer\_texts](https://repo.masters-masters.com/en/repos/mim-solutions/bert_for_longer_texts)

mim-solutions/bert\_for\_longer\_texts has 145 stars on GitHub. Its RepoMasters card: Prototype tier. BERT classification model for processing texts longer than…

| Field | Value |
| --- | --- |
| Owner | [mim-solutions](https://repo.masters-masters.com/en/owners/mim-solutions) |
| Stars | 145 |
| Forks | 33 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | None |
| Created | 2022 |
| Topics | nlp, natural-language-processing, bert, text-classification, transfer-learning, transformers, deep-learning, machine-learning, pytorch, roberta |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [mim-solutions/bert\_for\_longer\_texts](https://github.com/mim-solutions/bert_for_longer_texts) |

## Repository

BERT classification model for processing texts longer than 512 tokens. Text is first divided into smaller chunks and after feeding them to BERT, intermediate results are pooled. The implementation allows fine-tuning.

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.