Put Transformers on Conda (#8918)
* conda * Guide * correct tag * Update README.md Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update docs/source/installation.md Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Sylvain's comments Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
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$PYTHON setup.py install # Python command to install the script.
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{% set name = "transformers" %}
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package:
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name: "{{ name|lower }}"
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version: "{{ TRANSFORMERS_VERSION }}"
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source:
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path: ../../
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build:
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noarch: python
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requirements:
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host:
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- python
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- pip
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- numpy
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- dataclasses
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- packaging
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- filelock
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- requests
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- tqdm >=4.27
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- sacremoses
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- regex !=2019.12.17
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- protobuf
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- tokenizers ==0.9.4
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run:
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- python
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- numpy
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- dataclasses
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- packaging
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- filelock
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- requests
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- tqdm >=4.27
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- sacremoses
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- regex !=2019.12.17
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- protobuf
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- tokenizers ==0.9.4
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test:
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imports:
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- transformers
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about:
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home: https://huggingface.co
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license: Apache License 2.0
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license_file: LICENSE
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summary: "🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0."
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name: Release - Conda
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on:
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push:
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tags:
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- v*
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env:
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ANACONDA_API_TOKEN: ${{ secrets.ANACONDA_API_TOKEN }}
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jobs:
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build_and_package:
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runs-on: ubuntu-latest
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defaults:
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run:
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shell: bash -l {0}
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steps:
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- name: Checkout repository
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uses: actions/checkout@v1
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- name: Install miniconda
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uses: conda-incubator/setup-miniconda@v2
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with:
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auto-update-conda: true
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auto-activate-base: false
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activate-environment: "build-transformers"
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channels: huggingface
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- name: Setup conda env
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run: |
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conda install -c defaults anaconda-client conda-build
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- name: Extract version
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run: echo "TRANSFORMERS_VERSION=`python setup.py --version`" >> $GITHUB_ENV
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- name: Build conda packages
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run: |
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conda info
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conda build .github/conda
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- name: Upload to Anaconda
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run: anaconda upload `conda build .github/conda --output` --force
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README.md
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README.md
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@ -137,14 +137,16 @@ The model itself is a regular [Pytorch `nn.Module`](https://pytorch.org/docs/sta
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## Installation
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### With pip
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This repository is tested on Python 3.6+, PyTorch 1.0.0+ (PyTorch 1.3.1+ for [examples](https://github.com/huggingface/transformers/tree/master/examples)) and TensorFlow 2.0.
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You should install 🤗 Transformers in a [virtual environment](https://docs.python.org/3/library/venv.html). If you're unfamiliar with Python virtual environments, check out the [user guide](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/).
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First, create a virtual environment with the version of Python you're going to use and activate it.
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Then, you will need to install one of, or both, TensorFlow 2.0 and PyTorch.
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Please refer to [TensorFlow installation page](https://www.tensorflow.org/install/pip#tensorflow-2.0-rc-is-available) and/or [PyTorch installation page](https://pytorch.org/get-started/locally/#start-locally) regarding the specific install command for your platform.
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Then, you will need to install at least one of TensorFlow 2.0, PyTorch or Flax.
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Please refer to [TensorFlow installation page](https://www.tensorflow.org/install/pip#tensorflow-2.0-rc-is-available), [PyTorch installation page](https://pytorch.org/get-started/locally/#start-locally) regarding the specific install command for your platform and/or [Flax installation page](https://github.com/google/flax#quick-install).
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When TensorFlow 2.0 and/or PyTorch has been installed, 🤗 Transformers can be installed using pip as follows:
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If you'd like to play with the examples, you must [install the library from source](https://huggingface.co/transformers/installation.html#installing-from-source).
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### With conda
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Since Transformers version v4.0.0, we now have a conda channel: `huggingface`.
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🤗 Transformers can be installed using conda as follows:
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```shell script
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conda install -c huggingface transformers
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```
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Follow the installation pages of TensorFlow, PyTorch or Flax to see how to install them with conda.
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## Models architectures
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**[All the model checkpoints](https://huggingface.co/models)** provided by 🤗 Transformers are seamlessly integrated from the huggingface.co [model hub](https://huggingface.co) where they are uploaded directly by [users](https://huggingface.co/users) and [organizations](https://huggingface.co/organizations).
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## Installation with pip
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First you need to install one of, or both, TensorFlow 2.0 and PyTorch.
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Please refer to [TensorFlow installation page](https://www.tensorflow.org/install/pip#tensorflow-2.0-rc-is-available)
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and/or [PyTorch installation page](https://pytorch.org/get-started/locally/#start-locally) regarding the specific
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install command for your platform.
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Please refer to [TensorFlow installation page](https://www.tensorflow.org/install/pip#tensorflow-2.0-rc-is-available),
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[PyTorch installation page](https://pytorch.org/get-started/locally/#start-locally) and/or
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[Flax installation page](https://github.com/google/flax#quick-install)
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regarding the specific install command for your platform.
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When TensorFlow 2.0 and/or PyTorch has been installed, 🤗 Transformers can be installed using pip as follows:
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pip install transformers[tf-cpu]
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```
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or 🤗 Transformers and Flax in one line with:
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```bash
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pip install transformers[flax]
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```
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To check 🤗 Transformers is properly installed, run the following command:
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```bash
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to check 🤗 Transformers is properly installed.
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## With conda
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Since Transformers version v4.0.0, we now have a conda channel: `huggingface`.
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🤗 Transformers can be installed using conda as follows:
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```
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conda install -c huggingface transformers
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```
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Follow the installation pages of TensorFlow, PyTorch or Flax to see how to install them with conda.
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## Caching models
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This library provides pretrained models that will be downloaded and cached locally. Unless you specify a location with
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