# Lightweight RoBERTa

This model is a lightweight natural language inference model based on DistilRoBERTa, supporting zero-shot classification tasks.

This model is a fine-tuned version of distilroberta-base on the wikitext2 dataset, primarily used for text generation tasks.

A fine-tuned model based on distilroberta-base, suitable for specific NLP tasks

Text embedding model fine-tuned from all-distilroberta-v1, trained for 10 epochs with a validation loss of 0.0044

A fine-tuned version based on the distilroberta-base model, suitable for text-related tasks

This model is a fine-tuned version of distilroberta-base on the wikitext2 dataset, primarily used for text generation tasks.

A QA model fine-tuned on SQuAD2.0 dataset based on distilroberta-base, supporting unanswerable questions

envibert is a bilingual model based on the RoBERTa architecture, supporting Vietnamese and English processing, optimized for production environments.

A Q&A model fine-tuned on the SQuAD v2 dataset based on DistilRoBERTa-base, featuring lightweight and efficient characteristics.

CodeBERTaPy is a RoBERTa-like model trained on GitHub's CodeSearchNet dataset specifically for Python language, designed for code optimization.

A lightweight RoBERTa variant trained on 5 million American English child-directed corpora, specifically designed for language acquisition research

This is a model fine-tuned on a tweet hate speech detection dataset, designed to identify and classify hate speech on social media.

A named entity recognition model based on DistilRoBERTa-base, fine-tuned on the wikiann and conll2003 datasets, supporting 4-class entity recognition.

This model is a fine-tuned version of distilroberta-base on the wikitext2 dataset, primarily used for text generation tasks.

This is a news classification model fine-tuned on the AG News dataset based on the distilroberta-base model, achieving an accuracy of 0.94 on the test set.

Named entity recognition model fine-tuned on the CoNLL2003 dataset based on distilroberta-base

BabyBERTa is a lightweight version of RoBERTa, trained on child-directed input and specifically designed for language acquisition research.

BabyBERTa is a lightweight version based on RoBERTa, specifically designed for language acquisition research, trained on a 5-million-word corpus of American English child-directed input.

This model is a fine-tuned version of distilroberta-base on an unknown dataset, primarily used for text processing tasks.

A lightweight RoBERTa fill-mask model primarily trained on Greek tweets

This model is a fine-tuned version of distilroberta-base on the wikitext2 dataset, primarily designed for text generation tasks.

A fine-tuned version of the distilroberta-base model on the wikitext2 dataset, suitable for text-related tasks