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View details ↗bert-base-dutch-cased
GroNLPWietse de Vries • Andreas van Cranenburgh • Arianna Bisazza • Tommaso Caselli • Gertjan van Noord • Malvina Nissim **WARNING:** The vocabulary size of BERTje has changed in 2021. If you use an older fine-tuned model and experience problems with the `GroNLP/bert-base-dutch-cased` tokenizer, use use the following tokenizer: The arXiv paper lists benchmarks. Here are a couple of comparisons between BERTje, multilingual BERT, BERT-NL and RobBERT that were done after writing the paper. Unlike some other comparisons, the fine-tuning procedures for these benchmarks are identical for each pre-trained model. You may be able to achieve higher scores for individual models by optimizing fine-tuning procedures.
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View details ↗gpt2-small-dutch
GroNLPThis model is based on the small OpenAI GPT-2 (`gpt2`) model. For details, check out our paper on arXiv and the code on Github. - `gpt2-small-dutch-embeddings`: Small model size with only retrained lexical embeddings. - `gpt2-small-dutch`: Small model size with retrained lexical embeddings and additional fine-tuning of the full model. (**Recommended**) - `gpt2-medium-dutch-embeddings`: Medium model size with only retrained lexical embeddings.
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View details ↗gpt2-small-italian
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View details ↗hateBERT
GroNLPHateBERT is an English pre-trained BERT model obtained by further training the English BERT base uncased model with more than 1 million posts from banned communites from Reddit. The model has been developed as a collaboration between the University of Groningen, the university of Turin, and the University of Passau. For details, check out the paper presented at WOAH 2021. The code and the fine-tuned models are available on OSF. Fine-tuned models have a different licence, check the dedicated repository.
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View details ↗Groot-19B-A3B-261023
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View details ↗Groot-19B-A3B-261023-GGUF
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View details ↗Groot-65B-A6B-261023-GGUF
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View details ↗Bonsai-2-27B-PQ2_0-MTP-GGUF
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View details ↗No matching models
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