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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README.md
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# FERNET-C5
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FERNET-C5 (**F**lexible **E**mbedding **R**epresentation **NET**work) is a monolingual Czech BERT-base model pre-trained from 93GB of Czech Colossal Clean Crawled Corpus (C5). See our paper for details.
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## Paper
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https://link.springer.com/chapter/10.1007/978-3-030-89579-2_3
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# FERNET-C5
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FERNET-C5 (**F**lexible **E**mbedding **R**epresentation **NET**work) is a monolingual Czech BERT-base model pre-trained from 93GB of Czech Colossal Clean Crawled Corpus (C5). See our paper for details.
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We released also a successor of this model based on the RoBERTa architecture [fav-kky/FERNET-C5-RoBERTa](https://huggingface.co/fav-kky/FERNET-C5-RoBERTa).
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## Paper
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https://link.springer.com/chapter/10.1007/978-3-030-89579-2_3
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