A RetroSearch Logo

Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

Search Query:

Showing content from https://github.com/pytorch/text below:

pytorch/text: Models, data loaders and abstractions for language processing, powered by PyTorch

WARNING: TorchText development is stopped and the 0.18 release (April 2024) will be the last stable release of the library.

This repository consists of:

We recommend Anaconda as a Python package management system. Please refer to pytorch.org for the details of PyTorch installation. The following are the corresponding torchtext versions and supported Python versions.

Version Compatibility PyTorch version torchtext version Supported Python version nightly build main >=3.8, <=3.11 2.3.0 0.18.0 >=3.8, <=3.11 2.2.0 0.17.0 >=3.8, <=3.11 2.1.0 0.16.0 >=3.8, <=3.11 2.0.0 0.15.0 >=3.8, <=3.11 1.13.0 0.14.0 >=3.7, <=3.10 1.12.0 0.13.0 >=3.7, <=3.10 1.11.0 0.12.0 >=3.6, <=3.9 1.10.0 0.11.0 >=3.6, <=3.9 1.9.1 0.10.1 >=3.6, <=3.9 1.9 0.10 >=3.6, <=3.9 1.8.1 0.9.1 >=3.6, <=3.9 1.8 0.9 >=3.6, <=3.9 1.7.1 0.8.1 >=3.6, <=3.9 1.7 0.8 >=3.6, <=3.8 1.6 0.7 >=3.6, <=3.8 1.5 0.6 >=3.5, <=3.8 1.4 0.5 2.7, >=3.5, <=3.8 0.4 and below 0.2.3 2.7, >=3.5, <=3.8

Using conda:

conda install -c pytorch torchtext

Using pip:

pip install torchtext

If you want to use English tokenizer from SpaCy, you need to install SpaCy and download its English model:

pip install spacy
python -m spacy download en_core_web_sm

Alternatively, you might want to use the Moses tokenizer port in SacreMoses (split from NLTK). You have to install SacreMoses:

pip install sacremoses

For torchtext 0.5 and below, sentencepiece:

conda install -c powerai sentencepiece

To build torchtext from source, you need git, CMake and C++11 compiler such as g++.:

git clone https://github.com/pytorch/text torchtext
cd torchtext
git submodule update --init --recursive

# Linux
python setup.py clean install

# OSX
CC=clang CXX=clang++ python setup.py clean install

# or ``python setup.py develop`` if you are making modifications.

Note

When building from source, make sure that you have the same C++ compiler as the one used to build PyTorch. A simple way is to build PyTorch from source and use the same environment to build torchtext. If you are using the nightly build of PyTorch, checkout the environment it was built with conda (here) and pip (here).

Additionally, datasets in torchtext are implemented using the torchdata library. Please take a look at the installation instructions to download the latest nightlies or install from source.

Find the documentation here.

The datasets module currently contains:

The library currently consist of following pre-trained models:

The transforms module currently support following scriptable tokenizers:

To get started with torchtext, users may refer to the following tutorial available on PyTorch website.

This is a utility library that downloads and prepares public datasets. We do not host or distribute these datasets, vouch for their quality or fairness, or claim that you have license to use the dataset. It is your responsibility to determine whether you have permission to use the dataset under the dataset's license.

If you're a dataset owner and wish to update any part of it (description, citation, etc.), or do not want your dataset to be included in this library, please get in touch through a GitHub issue. Thanks for your contribution to the ML community!

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4