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setup.py
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setup.py
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# Copyright (c) Meta Platforms, Inc. and affiliates
# All rights reserved.
#
# This source code is licensed under the license found in the
# MIT_LICENSE file in the root directory of this source tree.
from setuptools import find_packages, setup
setup(
name="seamless_communication",
version="1.0.0",
packages=find_packages(where="src"),
package_dir={"": "src"},
package_data={"": ["py.typed", "cards/*.yaml"]},
description="SeamlessM4T -- Massively Multilingual & Multimodal Machine Translation Model",
long_description=open("README.md", encoding="utf-8").read(),
long_description_content_type="text/markdown",
readme="README.md",
python_requires=">=3.8",
author="Fundamental AI Research (FAIR) at Meta",
url="https://github.com/facebookresearch/seamless_communication",
license="Creative Commons",
install_requires=[
"datasets==2.18.0",
"fairseq2==0.2.*",
"fire",
"librosa",
"openai-whisper",
"simuleval~=1.1.3",
"sonar-space==0.2.*",
"soundfile",
"scipy",
"torchaudio",
"tqdm",
],
entry_points={
"console_scripts": [
"m4t_evaluate=seamless_communication.cli.m4t.evaluate.evaluate:main",
"m4t_predict=seamless_communication.cli.m4t.predict.predict:main",
"m4t_finetune=seamless_communication.cli.m4t.finetune.finetune:main",
"m4t_prepare_dataset=seamless_communication.cli.m4t.finetune.dataset:main",
"m4t_audio_to_units=seamless_communication.cli.m4t.audio_to_units.audio_to_units:main",
"expressivity_evaluate=seamless_communication.cli.expressivity.evaluate.evaluate:main",
"expressivity_predict=seamless_communication.cli.expressivity.predict.predict:main",
"streaming_evaluate=seamless_communication.cli.streaming.evaluate:main",
],
},
include_package_data=True,
)