Instructions to use sdadas/polish-roberta-base-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sdadas/polish-roberta-base-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="sdadas/polish-roberta-base-v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sdadas/polish-roberta-base-v1") model = AutoModelForMaskedLM.from_pretrained("sdadas/polish-roberta-base-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from sdadas/polish-roberta-base-v1: direct link, hf CLI and curl.
- Browser
- Download file 780 Bytes
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https://huggingface.co/sdadas/polish-roberta-base-v1/resolve/main/README.md
- Command line
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hf download hf://sdadas/polish-roberta-base-v1/README.md
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curl -L -o README.md https://huggingface.co/sdadas/polish-roberta-base-v1/resolve/main/README.md
780 Bytes
metadata
language: pl
license: apache-2.0
polish-roberta-base-v1
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 and in the publication Pre-training polish transformer-based language models at scale.
Citation
@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}
}