Welcome to the PyTorch NLP guide! This page provides an overview of the PyTorch NLP library, including its features, installation, and basic usage.

Features

PyTorch NLP is a library that provides easy-to-use and efficient tools for natural language processing (NLP) with PyTorch. It includes:

  • Tokenization
  • Word embeddings
  • Pre-trained models
  • Text classification
  • Named entity recognition
  • Sequence labeling
  • More...

Installation

To install PyTorch NLP, you can use pip:

pip install torch-nlp

Basic Usage

Here's a simple example of using PyTorch NLP to tokenize a sentence:

from torch_nlp import tokenizer

# Initialize the tokenizer
tokenizer = tokenizer.BertTokenizer()

# Tokenize a sentence
tokens = tokenizer.tokenize("Hello, world!")

print(tokens)

Further Reading

For more information on PyTorch NLP, please visit the official documentation.

Note: This guide is a starting point for learning PyTorch NLP. For more advanced topics, consider exploring the following resources:

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