text stringlengths 0 9.36M |
|---|
test: |
python -m pytest -n auto --dist=loadfile -s -v ./tests/ |
# Run the adapter tests |
test-adapters: |
python -m pytest -n auto --dist=loadfile -s -v ./tests_adapters/ |
test-adapter-methods: |
python -m pytest --ignore ./tests_adapters/models -n auto --dist=loadfile -s -v ./tests_adapters/ |
test-adapter-models: |
python -m pytest -n auto --dist=loadfile -s -v ./tests_adapters/models |
# Run tests for examples |
test-examples: |
python -m pytest -n auto --dist=loadfile -s -v ./examples/pytorch/ |
# Run tests for SageMaker DLC release |
test-sagemaker: # install sagemaker dependencies in advance with pip install .[sagemaker] |
TEST_SAGEMAKER=True python -m pytest -n auto -s -v ./tests/sagemaker |
# Release stuff |
pre-release: |
python utils/release.py |
pre-patch: |
python utils/release.py --patch |
post-release: |
python utils/release.py --post_release |
post-patch: |
python utils/release.py --post_release --patch |
File: README.md |
Contents: |
<!--- |
Copyright 2020 The AdapterHub Team. All rights reserved. |
Licensed under the Apache License, Version 2.0 (the "License"); |
you may not use this file except in compliance with the License. |
You may obtain a copy of the License at |
http://www.apache.org/licenses/LICENSE-2.0 |
Unless required by applicable law or agreed to in writing, software |
distributed under the License is distributed on an "AS IS" BASIS, |
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
See the License for the specific language governing permissions and |
limitations under the License. |
--> |
<p align="center"> |
<img style="vertical-align:middle" src="https://raw.githubusercontent.com/Adapter-Hub/adapter-transformers/master/adapter_docs/logo.png" /> |
</p> |
<h1 align="center"> |
<span>adapter-transformers</span> |
</h1> |
<h3 align="center"> |
A friendly fork of HuggingFace's <i>Transformers</i>, adding Adapters to PyTorch language models |
</h3> |
 |
[](https://github.com/adapter-hub/adapter-transformers/blob/master/LICENSE) |
[](https://pypi.org/project/adapter-transformers/) |
`adapter-transformers` is an extension of [HuggingFace's Transformers](https://github.com/huggingface/transformers) library, integrating adapters into state-of-the-art language models by incorporating **[AdapterHub](https://adapterhub.ml)**, a central repository for pre-trained adapter modules. |
_💡 Important: This library can be used as a drop-in replacement for HuggingFace Transformers and regularly synchronizes new upstream changes. |
Thus, most files in this repository are direct copies from the HuggingFace Transformers source, modified only with changes required for the adapter implementations._ |
## Installation |
`adapter-transformers` currently supports **Python 3.8+** and **PyTorch 1.12.1+**. |
After [installing PyTorch](https://pytorch.org/get-started/locally/), you can install `adapter-transformers` from PyPI ... |
``` |
pip install -U adapter-transformers |
``` |
... or from source by cloning the repository: |
``` |
git clone https://github.com/adapter-hub/adapter-transformers.git |
cd adapter-transformers |
pip install . |
``` |
## Getting Started |
HuggingFace's great documentation on getting started with _Transformers_ can be found [here](https://huggingface.co/transformers/index.html). `adapter-transformers` is fully compatible with _Transformers_. |
To get started with adapters, refer to these locations: |
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