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Awesome GitHub RepositoriesContextual Embedding Generators
Engines that map tokens to vector spaces based on usage context.
Distinguishing note: Focuses on the component identity as an embedding generator.
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Awesome Contextual Embedding Generators GitHub Repositories
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- google-research/bert
google-research/bert
39,869View on GitHubThis project is a transformer-based language model and natural language processing toolkit designed to generate deep contextual representations of text. By utilizing a transformer-based encoder architecture, the system processes input sequences through stacked self-attention layers to capture the semantic meaning of tokens based on their surrounding sentence structure. The model distinguishes itself through bidirectional contextual processing, which analyzes text in both directions simultaneously, and masked language modeling, which trains the system by predicting hidden tokens within a seque
Maps input tokens into high-dimensional vector spaces based on their specific usage within a surrounding sentence.
Pythongooglenatural-language-processingnatural-language-understanding
