TorchText
summary
TorchText provides reusable NLP building blocks, new datasets (beta/nightly), and C++-backed transforms that convert raw text to tensors while supporting DataLoader and samplers for production. Integrations include torchscript and quantization plus support for distributed data parallel and mobile workflows. A new multihead attention container exposes incremental decoding, broadcasting, and pluggable projection/score hooks so Transformer experiments drop in and scale; tutorials and dataset loaders are available and the C++ JIT-friendly extensions target lower-latency production use.
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chapters (8)
- 0:00Introduction
- 0:47Why TorchText
- 2:51New Data Sets
- 3:39Data Pipeline
- 5:17NLP Module
- 6:32Custom Components
- 7:05Text Tutorials
- 7:38Outro
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