We cross-validated four pretrained Bidirectional Encoder Representations from Transformers (BERT)–based models—BERT, BioBERT, ClinicalBERT, and MedBERT—by fine-tuning them on 90% of 3,261 sentences ...
Background: Artificial intelligence (AI) can diagnose a wide array of cardiac conditions from electrocardiograms (ECGs). Wearable and portable ECG devices may enable expanded AI-based screening for ...
Why was a new multilingual encoder needed? XLM-RoBERTa (XLM-R) has dominated multilingual NLP for more than 5 years, an unusually long reign in AI research. While encoder-only models like BERT and ...
The recent release of ModernBERT by LightOn and AnswerAI aims at providing the best base model that can be then used in different industry verticals. Efficient Continued Pre-Training, Streamlined for ...
no bugs hereNot a bug, but a workflow or environment issueNot a bug, but a workflow or environment issue I was trying to use Apply AnimateDiff+CameraCtrl Model node ...
Abstract: Address event representation (AER) object recognition task has attracted extensive attention in neuromorphic vision processing. The spike-based and event-driven computation inherent in the ...
It takes 10-20 min to load up torch, checkpoints, etc each when using 2 GPUs. The time grows with more GPUs. It otherwise only takes a couple minutes if it were 1 GPU. I suspect it's because of ...
Encoder models like BERT and RoBERTa have long been cornerstones of natural language processing (NLP), powering tasks such as text classification, retrieval, and toxicity detection. However, while ...
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