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  1. huggingface.co › docs › transformersRoBERTa - Hugging Face

    Constructs a RoBERTa tokenizer, derived from the GPT-2 tokenizer, using byte-level Byte-Pair-Encoding. This tokenizer has been trained to treat spaces like parts of the tokens (a bit like sentencepiece) so a word will

  2. keras.io › api › keras_nlpRobertaTokenizer - Keras

    Learn how to use a RoBERTa tokenizer with Byte-Pair Encoding subword segmentation in Keras NLP. See examples of tokenization, detokenization, and loading presets for different RoBERTa models.

  3. medium.com › analytics-vidhya › create-a-tokenizer-and-train-a-huggingface-robertaCreate a Tokenizer and Train a Huggingface RoBERTa Model from ......

    15 de ago. de 2021 · Create and train a byte-level, Byte-pair encoding tokenizer with the same special tokens as RoBERTa; Train a RoBERTa model from scratch using Masked Language Modeling, MLM.

  4. keras.io › api › keras_nlpRoBERTa - Keras

    Learn how to use RoBERTa, a robustly optimized BERT pretraining approach, with Keras NLP. Find out how to access models, tokenizers, preprocessing layers and presets for RoBERTa.

  5. pytorch.org › hub › pytorch_fairseq_robertaRoBERTa | PyTorch

    RoBERTa builds on BERT’s language masking strategy and modifies key hyperparameters in BERT, including removing BERT’s next-sentence pretraining objective, and training with much larger mini-batches and learning rates.