Instructions to use sdadas/polish-roberta-large-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sdadas/polish-roberta-large-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="sdadas/polish-roberta-large-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sdadas/polish-roberta-large-v2") model = AutoModelForMaskedLM.from_pretrained("sdadas/polish-roberta-large-v2") - Notebooks
- Google Colab
- Kaggle
| language: pl | |
| license: apache-2.0 | |
| <h1 align="center">polish-roberta-large-v2</h1> | |
| An encoder model based on the RoBERTa architecture, pre-trained on a large corpus of Polish texts. | |
| More information can be found in our [GitHub repository](https://github.com/sdadas/polish-roberta) and in the publication [Pre-training polish transformer-based language models at scale](https://arxiv.org/pdf/2006.04229). | |
| ## Citation | |
| ```bibtex | |
| @inproceedings{dadas2020pre, | |
| title={Pre-training polish transformer-based language models at scale}, | |
| author={Dadas, S{\l}awomir and Pere{\l}kiewicz, Micha{\l} and Po{\'s}wiata, Rafa{\l}}, | |
| booktitle={International Conference on Artificial Intelligence and Soft Computing}, | |
| pages={301--314}, | |
| year={2020}, | |
| organization={Springer} | |
| } | |
| ``` |