Instructions to use fav-kky/FERNET-C5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fav-kky/FERNET-C5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="fav-kky/FERNET-C5")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("fav-kky/FERNET-C5") model = AutoModelForMaskedLM.from_pretrained("fav-kky/FERNET-C5") - Notebooks
- Google Colab
- Kaggle
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# FRENET-C5
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FERNET-C5 is a monolingual Czech BERT model pre-trained from 93GB of filtered Czech Common Crawl dataset (C5).
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Preprint of our paper is available at https://arxiv.org/abs/2107.10042.
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# FRENET-C5
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FERNET-C5 is a monolingual Czech BERT-base model pre-trained from 93GB of filtered Czech Common Crawl dataset (C5).
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Preprint of our paper is available at https://arxiv.org/abs/2107.10042.
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