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https://github.com/conda-forge/pytorch-pretrained-bert-feedstock

A conda-smithy repository for pytorch-pretrained-bert.
https://github.com/conda-forge/pytorch-pretrained-bert-feedstock

Last synced: about 1 month ago
JSON representation

A conda-smithy repository for pytorch-pretrained-bert.

Host: GitHub
URL: https://github.com/conda-forge/pytorch-pretrained-bert-feedstock
Owner: conda-forge
License: bsd-3-clause
Created: 2018-12-20T21:30:07.000Z (almost 6 years ago)
Default Branch: main
Last Pushed: 2024-05-12T18:30:30.000Z (7 months ago)
Last Synced: 2024-10-30T02:47:01.523Z (about 1 month ago)
Size: 46.9 KB
Stars: 0
Watchers: 7
Forks: 5
Open Issues: 3
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
- Codeowners: .github/CODEOWNERS

Awesome Lists containing this project

awesome-bert - conda-forge/pytorch-pretrained-bert-feedstock - smithy repository for pytorch-pretrained-bert. , (implement of BERT besides tensorflow:)

README

        About pytorch-pretrained-bert-feedstock

=======================================

Feedstock license: [BSD-3-Clause](https://github.com/conda-forge/pytorch-pretrained-bert-feedstock/blob/main/LICENSE.txt)

Home: https://github.com/huggingface/pytorch-pretrained-BERT

Package license: Apache-2.0

Summary: PyTorch version of Google AI BERT model with script to load Google pre-trained models

This repository contains op-for-op PyTorch reimplementations, pre-trained

models and fine-tuning examples for:

  - Google's BERT model,

  - OpenAI's GPT model,

  - Google/CMU's Transformer-XL model, and

  - OpenAI's GPT-2 model.

These implementations have been tested on several datasets (see the

examples) and should match the performances of the associated TensorFlow

implementations (e.g. ~91 F1 on SQuAD for BERT, ~88 F1 on RocStories for

OpenAI GPT and ~18.3 perplexity on WikiText 103 for the Transformer-XL).

Current build status

====================

    

  

    Azure

    

      

        

          

            

          

        

        

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Current release info

====================

| Name | Downloads | Version | Platforms |

| --- | --- | --- | --- |

| [![Conda Recipe](https://img.shields.io/badge/recipe-pytorch--pretrained--bert-green.svg)](https://anaconda.org/conda-forge/pytorch-pretrained-bert) | [![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/pytorch-pretrained-bert.svg)](https://anaconda.org/conda-forge/pytorch-pretrained-bert) | [![Conda Version](https://img.shields.io/conda/vn/conda-forge/pytorch-pretrained-bert.svg)](https://anaconda.org/conda-forge/pytorch-pretrained-bert) | [![Conda Platforms](https://img.shields.io/conda/pn/conda-forge/pytorch-pretrained-bert.svg)](https://anaconda.org/conda-forge/pytorch-pretrained-bert) |

Installing pytorch-pretrained-bert

==================================

Installing `pytorch-pretrained-bert` from the `conda-forge` channel can be achieved by adding `conda-forge` to your channels with:

```

conda config --add channels conda-forge

conda config --set channel_priority strict

```

Once the `conda-forge` channel has been enabled, `pytorch-pretrained-bert` can be installed with `conda`:

```

conda install pytorch-pretrained-bert

```

or with `mamba`:

```

mamba install pytorch-pretrained-bert

```

It is possible to list all of the versions of `pytorch-pretrained-bert` available on your platform with `conda`:

```

conda search pytorch-pretrained-bert --channel conda-forge

```

or with `mamba`:

```

mamba search pytorch-pretrained-bert --channel conda-forge

```

Alternatively, `mamba repoquery` may provide more information:

```

# Search all versions available on your platform:

mamba repoquery search pytorch-pretrained-bert --channel conda-forge

# List packages depending on `pytorch-pretrained-bert`:

mamba repoquery whoneeds pytorch-pretrained-bert --channel conda-forge

# List dependencies of `pytorch-pretrained-bert`:

mamba repoquery depends pytorch-pretrained-bert --channel conda-forge

```

About conda-forge

=================

[![Powered by

NumFOCUS](https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A)](https://numfocus.org)

conda-forge is a community-led conda channel of installable packages.

In order to provide high-quality builds, the process has been automated into the

conda-forge GitHub organization. The conda-forge organization contains one repository

for each of the installable packages. Such a repository is known as a *feedstock*.

A feedstock is made up of a conda recipe (the instructions on what and how to build

the package) and the necessary configurations for automatic building using freely

available continuous integration services. Thanks to the awesome service provided by

[Azure](https://azure.microsoft.com/en-us/services/devops/), [GitHub](https://github.com/),

[CircleCI](https://circleci.com/), [AppVeyor](https://www.appveyor.com/),

[Drone](https://cloud.drone.io/welcome), and [TravisCI](https://travis-ci.com/)

it is possible to build and upload installable packages to the

[conda-forge](https://anaconda.org/conda-forge) [Anaconda-Cloud](https://anaconda.org/)

channel for Linux, Windows and OSX respectively.

To manage the continuous integration and simplify feedstock maintenance

[conda-smithy](https://github.com/conda-forge/conda-smithy) has been developed.

Using the ``conda-forge.yml`` within this repository, it is possible to re-render all of

this feedstock's supporting files (e.g. the CI configuration files) with ``conda smithy rerender``.

For more information please check the [conda-forge documentation](https://conda-forge.org/docs/).

Terminology

===========

**feedstock** - the conda recipe (raw material), supporting scripts and CI configuration.

**conda-smithy** - the tool which helps orchestrate the feedstock.

                   Its primary use is in the construction of the CI ``.yml`` files

                   and simplify the management of *many* feedstocks.

**conda-forge** - the place where the feedstock and smithy live and work to

                  produce the finished article (built conda distributions)

Updating pytorch-pretrained-bert-feedstock

==========================================

If you would like to improve the pytorch-pretrained-bert recipe or build a new

package version, please fork this repository and submit a PR. Upon submission,

your changes will be run on the appropriate platforms to give the reviewer an

opportunity to confirm that the changes result in a successful build. Once

merged, the recipe will be re-built and uploaded automatically to the

`conda-forge` channel, whereupon the built conda packages will be available for

everybody to install and use from the `conda-forge` channel.

Note that all branches in the conda-forge/pytorch-pretrained-bert-feedstock are

immediately built and any created packages are uploaded, so PRs should be based

on branches in forks and branches in the main repository should only be used to

build distinct package versions.

In order to produce a uniquely identifiable distribution:

 * If the version of a package **is not** being increased, please add or increase

   the [``build/number``](https://docs.conda.io/projects/conda-build/en/latest/resources/define-metadata.html#build-number-and-string).

 * If the version of a package **is** being increased, please remember to return

   the [``build/number``](https://docs.conda.io/projects/conda-build/en/latest/resources/define-metadata.html#build-number-and-string)

   back to 0.

Feedstock Maintainers

=====================

* [@CurtLH](https://github.com/CurtLH/)

* [@sodre](https://github.com/sodre/)