# Scientific Literature Analysis

A vision-language model fine-tuned on the PMC-OA dataset based on CLIP-ViT-L/14

This is a fine-tuned BERT-based language model for classifying NLP-related research papers according to concepts in the NLP taxonomy. It is a multi-label classifier capable of predicting concepts at all levels of the NLP taxonomy.

This is a BERT-based pre-trained language model for the biomedical domain, suitable for processing biomedical text data.

A fine-tuned model based on BioBERT for the biomedical domain, achieving an F1 score of 0.8621 on specific tasks

This model is trained on the jnlpba dataset, fine-tuned based on the pre-trained PubMed version of RoBERTa, specifically designed to identify biomedical entities such as genes, DNA, RNA, and proteins

A model fine-tuned on biomedical domain text based on PubMedBERT, designed for PubMedQA tasks

RuBioRoBERTa is a RoBERTa model pretrained for Russian biomedical text, specifically designed for natural language processing tasks in the biomedical domain.