Multilingual
mdeberta-v3-base with 30k steps multi-task training on
mtasksource
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 to directly load a model for hundreds of tasks.
1!pip install tasknet, tasksource -q
2import tasknet as tn
3pipe=tn.load_pipeline(
4 'sileod/mdeberta-v3-base-tasksource-nli',
5 'miam/dihana')
6pipe(['si','como esta?'])
For more details, see
deberta-v3-base-tasksource-nli and replace tasksource by mtasksource.
For help integrating tasksource into your experiments, please contact
damien.sileo@inria.fr.
For more details, refer to this
article:
1@article{sileo2023tasksource,
2 title={tasksource: Structured Dataset Preprocessing Annotations for Frictionless Extreme Multi-Task Learning and Evaluation},
3 author={Sileo, Damien},
4 url= {https://arxiv.org/abs/2301.05948},
5 journal={arXiv preprint arXiv:2301.05948},
6 year={2023}
7}