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--- |
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license: apache-2.0 |
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tags: |
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- mdeberta-v3-base |
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- text-classification |
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- nli |
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- natural-language-inference |
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- multilingual |
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- multitask |
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- multi-task |
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- pipeline |
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- extreme-multi-task |
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- extreme-mtl |
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- tasksource |
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- zero-shot |
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- rlhf |
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datasets: |
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- xnli |
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- metaeval/xnli |
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- americas_nli |
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- MoritzLaurer/multilingual-NLI-26lang-2mil7 |
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- stsb_multi_mt |
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- paws-x |
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- miam |
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- strombergnlp/x-stance |
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- tyqiangz/multilingual-sentiments |
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- metaeval/universal-joy |
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- amazon_reviews_multi |
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- cardiffnlp/tweet_sentiment_multilingual |
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- strombergnlp/offenseval_2020 |
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- offenseval_dravidian |
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- nedjmaou/MLMA_hate_speech |
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- xglue |
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- ylacombe/xsum_factuality |
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- metaeval/x-fact |
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- pasinit/xlwic |
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- tasksource/oasst1_dense_flat |
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- papluca/language-identification |
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- wili_2018 |
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- exams |
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- xcsr |
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- xcopa |
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- juletxara/xstory_cloze |
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- Anthropic/hh-rlhf |
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- OpenAssistant/oasst1 |
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language: |
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- multilingual |
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- zh |
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- ja |
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- ar |
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- ko |
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- de |
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- fr |
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- es |
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- pt |
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- hi |
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- id |
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- it |
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- tr |
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- ru |
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- bn |
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- ur |
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- mr |
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- ta |
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- vi |
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- fa |
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- pl |
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- uk |
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- nl |
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- sv |
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- he |
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- sw |
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- ps |
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pipeline_tag: zero-shot-classification |
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--- |
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# Model Card for mDeBERTa-v3-base-tasksource-nli |
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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/src/tasksource/mtasks.py) |
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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. |
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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. |
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```python |
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!pip install tasknet, tasksource -q |
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import tasknet as tn |
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pipe=tn.load_pipeline( |
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'sileod/mdeberta-v3-base-tasksource-nli', |
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'miam/dihana') |
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pipe(['si','como esta?']) |
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``` |
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# Software |
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https://github.com/sileod/tasksource/ |
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https://github.com/sileod/tasknet/ |
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# Contact and citation |
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For help integrating tasksource into your experiments, please contact [[email protected]](mailto:[email protected]). |
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For more details, refer to this [article:](https://arxiv.org/abs/2301.05948) |
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```bib |
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@article{sileo2023tasksource, |
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title={tasksource: Structured Dataset Preprocessing Annotations for Frictionless Extreme Multi-Task Learning and Evaluation}, |
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author={Sileo, Damien}, |
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url= {https://arxiv.org/abs/2301.05948}, |
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journal={arXiv preprint arXiv:2301.05948}, |
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year={2023} |
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} |
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``` |
