This is the Linux app named torchtext whose latest release can be downloaded as Torchtext0.16.zip. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named torchtext with OnWorks for free.
Follow these instructions in order to run this app:
- 1. Downloaded this application in your PC.
- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 3. Upload this application in such filemanager.
- 4. Start the OnWorks Linux online or Windows online emulator or MACOS online emulator from this website.
- 5. From the OnWorks Linux OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 6. Download the application, install it and run it.
SCREENSHOTS:
torchtext
DESCRIPTION:
We recommend Anaconda as a Python package management system. Please refer to pytorch.org for the details of PyTorch installation. LTS versions are distributed through a different channel than the other versioned releases. Alternatively, you might want to use the Moses tokenizer port in SacreMoses (split from NLTK). You have to install SacreMoses. To build torchtext from source, you need git, CMake and C++11 compiler such as g++. 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, check out the environment it was built with conda (here) and pip (here). Text classification: SST2, AG_NEWS, SogouNews, DBpedia, YelpReviewPolarity, YelpReviewFull, YahooAnswers, AmazonReviewPolarity, AmazonReviewFull, IMDB, etc.
Features
- To build torchtext from source, you need git, CMake and C++11 compiler such as g++
- Language modeling: WikiText2, WikiText103, PennTreebank, EnWik9
- Machine translation: IWSLT2016, IWSLT2017, Multi30k
- Sequence tagging (e.g. POS/NER): UDPOS, CoNLL2000Chunking
- Question answering: SQuAD1, SQuAD2
- Model pre-training: CC-100
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/torchtext.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.