MoritzLaurer/multilingual-NLI-26lang-2mil7
Datasheet for the dataset: multilingual-NLI-26lang-2mil7 Dataset Summary This dataset contains 2 730 000 NLI text pairs in 26 languages spoken by more than 4 billion people. The dataset can be used to train models for multilingual NLI (Natural Language Inference) or zero-shot classification. The dataset is based on the English datasets MultiNLI, Fever-NLI, ANLI, LingNLI and WANLI and was created using the latest open-source machine translation models. The dataset… See the full description on the dataset page: https://huggingface.co/datasets/MoritzLaurer/multilingual-NLI-26lang-2mil7.
| Author / organization | MoritzLaurer |
|---|---|
| Downloads | 3.5K (as reported by Hugging Face) |
| Likes | 52 |
| Created | 17 August 2022 |
| Last updated at source | 22 August 2022 |
Popularity, last 3 days
3,501 now (-80 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Connected in the knowledge graph
- iara-project/BERTimbau-large-matryoshka-sts-ptModel · used to train
- onnx-community/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7-ONNXModel · used to train
- alexandrainst/scandi-nli-large-v2Model · used to train
- MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7Model · used to train
- alexandrainst/scandi-nli-largeModel · used to train
- alexandrainst/scandi-nli-smallModel · used to train
- iara-project/e5-large-matryoshka-sts-ptModel · used to train
- pkshatech/GLuCoSE-base-jaModel · used to train
- LazarusNLP/indobert-lite-base-p1-indonli-multilingual-nli-distil-mdebertaModel · used to train
Recent changes
- 16 Oct 2026 Description: Datasheet for the dataset: multilingual-NLI-26lang-2mil7 Dataset Summary This dataset contains 2 730 000 NLI text pairs in 26 languages spoken by more than 4 billion people. The dataset can be used to train models for multilingual NLI (Natu → Datasheet for the dataset: multilingual-NLI-26lang-2mil7 Dataset Summary This dataset contains 2 730 000 NLI text pairs in 26 languages spoken by more than 4 billion people. The dataset can be used to train models for multilingual NLI (Natu
Changes detected by Silytics between refreshes of the source.
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