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Awesome GitHub RepositoriesConfigurable Text Classifiers
Training deep-learning text classifiers from labeled utterances using configurable convolutional or self-attentive architectures.
Distinct from Text Classifier Construction: Distinct from Text Classifier Construction: focuses on training from labeled utterances with configurable architectures, not building from pretrained encoders.
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Awesome Configurable Text Classifiers GitHub Repositories
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- facebookresearch/pytext
facebookresearch/pytext
6,298在 GitHub 上查看PyText is an extensible PyTorch-based framework for building, training, and deploying custom natural language processing models, including text classifiers, sequence taggers, and intent-slot predictors. It provides a modular toolkit that allows developers to assemble these models using pluggable registries for model architectures, data formats, and tensorizers, all configurable through YAML files without requiring code changes. The framework distinguishes itself through its comprehensive support for the full NLP model lifecycle, from training to production inference. It includes pre-built neu
Trains deep-learning text classifiers from labeled utterances using configurable architectures.
Python
