Average Model Cost: $0.0000
Number of Runs: 44,375
Models by this creator
LinkBERT-large is a model for text classification tasks. It is a large-scale version of the LinkBERT model, which utilizes self-attention mechanisms to process text input. It has been trained on a large corpus of text and can be fine-tuned for specific classification tasks. The model is able to understand the semantic relationships between words and can make accurate predictions for various NLP tasks such as sentiment analysis, topic classification, and spam detection.
BioLinkBERT-base is a text classification model specifically trained for biomedical domain tasks. It is based on the BERT architecture and has been fine-tuned on a large dataset of biomedical literature. This model can be used for various natural language processing tasks such as entity recognition, relation extraction, and document classification in the biomedical domain. It has achieved high performance on benchmark datasets and can provide valuable insights for research and development in the field of biomedicine.