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2 changes: 1 addition & 1 deletion CONTRIBUTING.md
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Expand Up @@ -132,7 +132,7 @@ You will need basic `git` proficiency to contribute to
manual. Type `git --help` in a shell and enjoy! If you prefer books, [Pro
Git](https://git-scm.com/book/en/v2) is a very good reference.

You'll need **[Python 3.8](https://github.com/huggingface/transformers/blob/main/setup.py#L449)** or above to contribute to 🤗 Transformers. Follow the steps below to start contributing:
You'll need **[Python 3.9](https://github.com/huggingface/transformers/blob/main/setup.py#L449)** or above to contribute to 🤗 Transformers. Follow the steps below to start contributing:

1. Fork the [repository](https://github.com/huggingface/transformers) by
clicking on the **[Fork](https://github.com/huggingface/transformers/fork)** button on the repository's page. This creates a copy of the code
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -249,7 +249,7 @@ The model itself is a regular [Pytorch `nn.Module`](https://pytorch.org/docs/sta

### With pip

This repository is tested on Python 3.8+, Flax 0.4.1+, PyTorch 1.11+, and TensorFlow 2.6+.
This repository is tested on Python 3.9+, Flax 0.4.1+, PyTorch 1.11+, and TensorFlow 2.6+.

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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2 changes: 1 addition & 1 deletion docker/transformers-all-latest-gpu/Dockerfile
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@@ -1,4 +1,4 @@
FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04
FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu22.04
LABEL maintainer="Hugging Face"

ARG DEBIAN_FRONTEND=noninteractive
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2 changes: 1 addition & 1 deletion docker/transformers-pytorch-gpu/Dockerfile
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@@ -1,4 +1,4 @@
FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04
FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu22.04
LABEL maintainer="Hugging Face"

ARG DEBIAN_FRONTEND=noninteractive
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8 changes: 4 additions & 4 deletions docker/transformers-quantization-latest-gpu/Dockerfile
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@@ -1,4 +1,4 @@
FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu20.04
FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04
LABEL maintainer="Hugging Face"

ARG DEBIAN_FRONTEND=noninteractive
Expand All @@ -9,12 +9,12 @@ SHELL ["sh", "-lc"]
# The following `ARG` are mainly used to specify the versions explicitly & directly in this docker file, and not meant
# to be used as arguments for docker build (so far).

ARG PYTORCH='2.2.1'
ARG PYTORCH='2.4.1'
# Example: `cu102`, `cu113`, etc.
ARG CUDA='cu118'

RUN apt update
RUN apt install -y git libsndfile1-dev tesseract-ocr espeak-ng python python3-pip ffmpeg
RUN apt install -y git libsndfile1-dev tesseract-ocr espeak-ng python3 python3-pip ffmpeg
RUN python3 -m pip install --no-cache-dir --upgrade pip

ARG REF=main
Expand Down Expand Up @@ -53,7 +53,7 @@ RUN python3 -m pip install --no-cache-dir gguf

# Add autoawq for quantization testing
# >=v0.2.3 needed for compatibility with torch 2.2.1
RUN python3 -m pip install --no-cache-dir https://github.com/casper-hansen/AutoAWQ/releases/download/v0.2.3/autoawq-0.2.3+cu118-cp38-cp38-linux_x86_64.whl
RUN python3 -m pip install --no-cache-dir https://github.com/casper-hansen/AutoAWQ/releases/download/v0.2.3/autoawq-0.2.3+cu118-cp310-cp310-linux_x86_64.whl

# Add quanto for quantization testing
RUN python3 -m pip install --no-cache-dir optimum-quanto
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2 changes: 1 addition & 1 deletion docker/transformers-tensorflow-gpu/Dockerfile
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@@ -1,4 +1,4 @@
FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04
FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu22.04
LABEL maintainer="Hugging Face"

ARG DEBIAN_FRONTEND=noninteractive
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2 changes: 1 addition & 1 deletion docs/source/de/contributing.md
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Expand Up @@ -112,7 +112,7 @@ Bevor Sie irgendwelchen Code schreiben, empfehlen wir Ihnen dringend, die besteh

Sie benötigen grundlegende `git`-Kenntnisse, um zu 🤗 Transformers beizutragen. Obwohl `git` nicht das einfachste Werkzeug ist, hat es ein sehr gutes Handbuch. Geben Sie `git --help` in eine Shell ein und genießen Sie es! Wenn Sie Bücher bevorzugen, ist [Pro Git](https://git-scm.com/book/en/v2) eine gute Anlaufstelle.

Sie benötigen **[Python 3.8](https://github.com/huggingface/transformers/blob/main/setup.py#L426)** oder höher, um zu 🤗 Transformers beizutragen. Folgen Sie den nachstehenden Schritten, um mit dem Beitrag zu beginnen:
Sie benötigen **[Python 3.9](https://github.com/huggingface/transformers/blob/main/setup.py#L426)** oder höher, um zu 🤗 Transformers beizutragen. Folgen Sie den nachstehenden Schritten, um mit dem Beitrag zu beginnen:

1. Forken Sie das [Repository](https://github.com/huggingface/transformers), indem Sie auf den **[Fork](https://github.com/huggingface/transformers/fork)**-Button auf der Seite des Repositorys klicken. Dadurch wird eine Kopie des Codes auf Ihrem GitHub-Account erstellt.

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2 changes: 1 addition & 1 deletion docs/source/ko/contributing.md
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Expand Up @@ -113,7 +113,7 @@ python src/transformers/commands/transformers_cli.py env

🤗 Transformers에 기여하기 위해서는 기본적인 `git` 사용 능력이 필요합니다. `git`은 사용하기 쉬운 도구는 아니지만, 매우 훌륭한 매뉴얼을 제공합니다. 쉘(shell)에서 `git --help`을 입력하여 확인해보세요! 만약 책을 선호한다면, [Pro Git](https://git-scm.com/book/en/v2)은 매우 좋은 참고 자료가 될 것입니다.

🤗 Transformers에 기여하려면 **[Python 3.8](https://github.com/huggingface/transformers/blob/main/setup.py#L426)** 이상의 버전이 필요합니다. 기여를 시작하려면 다음 단계를 따르세요:
🤗 Transformers에 기여하려면 **[Python 3.9](https://github.com/huggingface/transformers/blob/main/setup.py#L426)** 이상의 버전이 필요합니다. 기여를 시작하려면 다음 단계를 따르세요:

1. 저장소 페이지에서 **[Fork](https://github.com/huggingface/transformers/fork)** 버튼을 클릭하여 저장소를 포크하세요. 이렇게 하면 코드의 복사본이 여러분의 GitHub 사용자 계정 아래에 생성됩니다.

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2 changes: 1 addition & 1 deletion docs/source/zh/contributing.md
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Expand Up @@ -112,7 +112,7 @@ python src/transformers/commands/transformers_cli.py env

要为 🤗 Transformers 做贡献,你需要基本的 `git` 使用技能。虽然 `git` 不是一个很容易使用的工具,但它提供了非常全面的手册,在命令行中输入 `git --help` 并享受吧!如果你更喜欢书籍,[Pro Git](https://git-scm.com/book/en/v2)是一本很好的参考书。

要为 🤗 Transformers 做贡献,你需要 **[Python 3.8](https://github.com/huggingface/transformers/blob/main/setup.py#L426)** 或更高版本。请按照以下步骤开始贡献:
要为 🤗 Transformers 做贡献,你需要 **[Python 3.9](https://github.com/huggingface/transformers/blob/main/setup.py#L426)** 或更高版本。请按照以下步骤开始贡献:

1. 点击[仓库](https://github.com/huggingface/transformers)页面上的 **[Fork](https://github.com/huggingface/transformers/fork)** 按钮,这会在你的 GitHub 账号下拷贝一份代码。

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5 changes: 2 additions & 3 deletions setup.py
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Expand Up @@ -150,7 +150,7 @@
"pytest>=7.2.0,<8.0.0",
"pytest-timeout",
"pytest-xdist",
"python>=3.8.0",
"python>=3.9.0",
"ray[tune]>=2.7.0",
"regex!=2019.12.17",
"requests",
Expand Down Expand Up @@ -451,7 +451,7 @@ def run(self):
zip_safe=False,
extras_require=extras,
entry_points={"console_scripts": ["transformers-cli=transformers.commands.transformers_cli:main"]},
python_requires=">=3.8.0",
python_requires=">=3.9.0",
install_requires=list(install_requires),
classifiers=[
"Development Status :: 5 - Production/Stable",
Expand All @@ -461,7 +461,6 @@ def run(self):
"License :: OSI Approved :: Apache Software License",
"Operating System :: OS Independent",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
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2 changes: 1 addition & 1 deletion src/transformers/dependency_versions_table.py
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Expand Up @@ -56,7 +56,7 @@
"pytest": "pytest>=7.2.0,<8.0.0",
"pytest-timeout": "pytest-timeout",
"pytest-xdist": "pytest-xdist",
"python": "python>=3.8.0",
"python": "python>=3.9.0",
"ray[tune]": "ray[tune]>=2.7.0",
"regex": "regex!=2019.12.17",
"requests": "requests",
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