| --- |
| license: apache-2.0 |
| tags: |
| - mdeberta-v3-base |
| - text-classification |
| - nli |
| - natural-language-inference |
| - multilingual |
| - multitask |
| - multi-task |
| - pipeline |
| - extreme-multi-task |
| - extreme-mtl |
| - tasksource |
| - zero-shot |
| - rlhf |
| datasets: |
| - xnli |
| - metaeval/xnli |
| - americas_nli |
| - MoritzLaurer/multilingual-NLI-26lang-2mil7 |
| - stsb_multi_mt |
| - paws-x |
| - miam |
| - strombergnlp/x-stance |
| - tyqiangz/multilingual-sentiments |
| - metaeval/universal-joy |
| - amazon_reviews_multi |
| - cardiffnlp/tweet_sentiment_multilingual |
| - strombergnlp/offenseval_2020 |
| - offenseval_dravidian |
| - nedjmaou/MLMA_hate_speech |
| - xglue |
| - ylacombe/xsum_factuality |
| - metaeval/x-fact |
| - pasinit/xlwic |
| - tasksource/oasst1_dense_flat |
| - papluca/language-identification |
| - wili_2018 |
| - exams |
| - xcsr |
| - xcopa |
| - juletxara/xstory_cloze |
| - Anthropic/hh-rlhf |
| - universal_dependencies |
| - tasksource/oasst1_pairwise_rlhf_reward |
| - OpenAssistant/oasst1 |
| language: |
| - multilingual |
| - zh |
| - ja |
| - ar |
| - ko |
| - de |
| - fr |
| - es |
| - pt |
| - hi |
| - id |
| - it |
| - tr |
| - ru |
| - bn |
| - ur |
| - mr |
| - ta |
| - vi |
| - fa |
| - pl |
| - uk |
| - nl |
| - sv |
| - he |
| - sw |
| - ps |
| pipeline_tag: zero-shot-classification |
| --- |
| |
| # Model Card for mDeBERTa-v3-base-tasksource-nli |
|
|
| Multilingual [mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) with 30k steps multi-task training on [mtasksource](https://github.com/sileod/tasksource/blob/main/mtasks.md) |
| This model can be used as a stable starting-point for further fine-tuning, or directly in zero-shot NLI model or a zero-shot pipeline. |
| In addition, you can use the provided [adapters](https://huggingface.co/sileod/mdeberta-v3-base-tasksource-adapters) to directly load a model for hundreds of tasks. |
| ```python |
| !pip install tasknet, tasksource -q |
| import tasknet as tn |
| pipe=tn.load_pipeline( |
| 'sileod/mdeberta-v3-base-tasksource-nli', |
| 'miam/dihana') |
| pipe(['si','como esta?']) |
| ``` |
|
|
| For more details, see [deberta-v3-base-tasksource-nli](https://huggingface.co/sileod/deberta-v3-base-tasksource-nli) and replace tasksource by mtasksource. |
|
|
| # Software |
| https://github.com/sileod/tasksource/ |
| https://github.com/sileod/tasknet/ |
|
|
| # Contact and citation |
| For help integrating tasksource into your experiments, please contact [damien.sileo@inria.fr](mailto:damien.sileo@inria.fr). |
|
|
| For more details, refer to this [article:](https://arxiv.org/abs/2301.05948) |
| ```bib |
| @article{sileo2023tasksource, |
| title={tasksource: Structured Dataset Preprocessing Annotations for Frictionless Extreme Multi-Task Learning and Evaluation}, |
| author={Sileo, Damien}, |
| url= {https://arxiv.org/abs/2301.05948}, |
| journal={arXiv preprint arXiv:2301.05948}, |
| year={2023} |
| } |
| ``` |
