Instructions to use mideind/IceBERT-ic3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mideind/IceBERT-ic3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mideind/IceBERT-ic3")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mideind/IceBERT-ic3") model = AutoModelForMaskedLM.from_pretrained("mideind/IceBERT-ic3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse files
README.md
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---
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language: is
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widget:
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- text: Má bjóða þér <mask> í kvöld?
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- text: Forseti <mask> er ágæt.
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- text: Súpan var <mask> á bragðið.
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tags:
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- roberta
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- icelandic
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- masked-lm
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- pytorch
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license: agpl-3.0
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---
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# IceBERT-ic3
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This model was trained with fairseq using the RoBERTa-base architecture. It is one of many models we have trained for Icelandic, see the paper referenced below for further details. The training data used is shown in the table below.
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| Dataset | Size | Tokens |
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|------------------------------------------------------|---------|--------|
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| Icelandic Common Crawl Corpus (IC3) | 4.9 GB | 824M |
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## Scitation
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The model is described in this paper [https://arxiv.org/abs/2201.05601](https://arxiv.org/abs/2201.05601). Please cite the paper if you make use of the model.
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```
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@article{DBLP:journals/corr/abs-2201-05601,
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author = {V{\'{e}}steinn Sn{\ae}bjarnarson and
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Haukur Barri S{\'{\i}}monarson and
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P{\'{e}}tur Orri Ragnarsson and
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Svanhv{\'{\i}}t Lilja Ing{\'{o}}lfsd{\'{o}}ttir and
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Haukur P{\'{a}}ll J{\'{o}}nsson and
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Vilhj{\'{a}}lmur {\TH}orsteinsson and
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Hafsteinn Einarsson},
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title = {A Warm Start and a Clean Crawled Corpus - {A} Recipe for Good Language
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Models},
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journal = {CoRR},
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volume = {abs/2201.05601},
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year = {2022},
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url = {https://arxiv.org/abs/2201.05601},
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eprinttype = {arXiv},
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eprint = {2201.05601},
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timestamp = {Thu, 20 Jan 2022 14:21:35 +0100},
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biburl = {https://dblp.org/rec/journals/corr/abs-2201-05601.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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```
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