Shypd.aiThe largest open index of AI toolsexBERT is an open-source visual analysis tool that explores learned representations in Transformer models. It allows users to visualize attention weights and contextual representations, aiding in understanding and debugging AI models.
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exBERT is an open-source visual analysis tool designed to help users explore and understand the learned attention weights and contextual representations within various Hugging Face Transformer models. It supports models like BERT, GPT2, DistilBERT, and ALBERT. Users can input sentences, visualize attention patterns as curved lines, and search embeddings across an annotated corpus. Key features include toggling visibility of attention to [CLS] and [SEP] tokens, interactively masking tokens to observe attention changes, and viewing model predictions. It also allows searching for contextual representations of tokens across layers and discovering linguistic features learned by specific heads, making it an invaluable resource for AI researchers and NLP developers.
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