osekilab / JCoLALinks
☆19Updated last year
Alternatives and similar repositories for JCoLA
Users that are interested in JCoLA are comparing it to the libraries listed below
Sorting:
- Code for COLING 2020 Paper☆13Updated 2 weeks ago
- Repository for JSICK☆44Updated 2 years ago
- ☆28Updated 5 months ago
- ☆17Updated 2 years ago
- This repository has implementations of data augmentation for NLP for Japanese.☆64Updated 2 years ago
- DIRECT: Direct and Indirect REsponses in Conversational Text Corpus☆16Updated 4 years ago
- Utility scripts for preprocessing Wikipedia texts for NLP☆77Updated last year
- AllenNLP integration for Shiba: Japanese CANINE model☆12Updated 4 years ago
- ☆37Updated 4 years ago
- Japanese Realistic Textual Entailment Corpus (NLP 2020, LREC 2020)☆76Updated 2 years ago
- Codes to pre-train Japanese T5 models☆40Updated 4 years ago
- Evidence-based Explanation Dataset (AACL-IJCNLP 2020)☆18Updated 4 years ago
- ☆16Updated 3 years ago
- A Japanese dependency parser based on BERT☆23Updated 2 years ago
- Japanese data from the Google UDT 2.0.☆28Updated 2 years ago
- ☆31Updated 7 years ago
- Annotated Fuman Kaitori Center Corpus☆18Updated last year
- Japanese semantic test suite (FraCaS counterpart and extensions)☆13Updated 10 months ago
- Funer is Rule based Named Entity Recognition tool.☆22Updated 3 years ago
- Wikipediaから作成した日本語名寄せデータセット☆35Updated 5 years ago
- Japanese instruction data (日本語指示データ)☆24Updated 2 years ago
- Pytorch implementation and pre-trained Japanese model for CANINE, the efficient character-level transformer.☆89Updated last year
- Flexible evaluation tool for language models☆51Updated this week
- 敬語変換タスクにおける評価用データセット☆21Updated 2 years ago
- A simple implementation of SimCSE☆77Updated 2 years ago
- japanese sentence segmentation library for python☆73Updated 2 years ago
- Use custom tokenizers in spacy-transformers☆16Updated 3 years ago
- Japanese tokenizer for Transformers☆79Updated last year
- 日本語テキストに対する wikification のためのソフトウェア☆16Updated 8 years ago
- The evaluation scripts of JMTEB (Japanese Massive Text Embedding Benchmark)☆72Updated last month