semvec/pypi-packages huggingface dataset:
ai-keji-dabenying-201912-202003 2023.2.15.0
AI科技大本营 201912-202003
Requires Python: >=3.6

# AI科技大本营 201912-202003

## 下载

### Docker

```
docker pull apachecn0/ai-keji-dabenying-201912-202003
docker run -tid -p <port>:80 apachecn0/ai-keji-dabenying-201912-202003
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install ai-keji-dabenying-201912-202003
ai-keji-dabenying-201912-202003 <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g ai-keji-dabenying-erlingyijiuyier-erlingerlinglingsan
ai-keji-dabenying-erlingyijiuyier-erlingerlinglingsan <port>
# 访问 http://localhost:{port} 查看文档
```
ai-keji-dabenying-201910-201912 2023.2.15.0
AI科技大本营 201910-201912
Requires Python: >=3.6

# AI科技大本营 201910-201912

## 下载

### Docker

```
docker pull apachecn0/ai-keji-dabenying-201910-201912
docker run -tid -p <port>:80 apachecn0/ai-keji-dabenying-201910-201912
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install ai-keji-dabenying-201910-201912
ai-keji-dabenying-201910-201912 <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g ai-keji-dabenying-erlingyijiuyiling-erlingyijiuyier
ai-keji-dabenying-erlingyijiuyiling-erlingyijiuyier <port>
# 访问 http://localhost:{port} 查看文档
```
ai-keji-dabenying-201908-201910 2023.2.15.0
AI科技大本营 201908-201910
Requires Python: >=3.6

# AI科技大本营 201908-201910

## 下载

### Docker

```
docker pull apachecn0/ai-keji-dabenying-201908-201910
docker run -tid -p <port>:80 apachecn0/ai-keji-dabenying-201908-201910
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install ai-keji-dabenying-201908-201910
ai-keji-dabenying-201908-201910 <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g ai-keji-dabenying-erlingyijiulingba-erlingyijiuyiling
ai-keji-dabenying-erlingyijiulingba-erlingyijiuyiling <port>
# 访问 http://localhost:{port} 查看文档
```
ai-keji-dabenying-201906-201908 2023.2.15.0
AI科技大本营 201906-201908
Requires Python: >=3.6

# AI科技大本营 201906-201908

## 下载

### Docker

```
docker pull apachecn0/ai-keji-dabenying-201906-201908
docker run -tid -p <port>:80 apachecn0/ai-keji-dabenying-201906-201908
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install ai-keji-dabenying-201906-201908
ai-keji-dabenying-201906-201908 <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g ai-keji-dabenying-erlingyijiulingliu-erlingyijiulingba
ai-keji-dabenying-erlingyijiulingliu-erlingyijiulingba <port>
# 访问 http://localhost:{port} 查看文档
```
brezn 0.1.0
Something layered on top of hydra.
Requires Python: >= 3.6

# brezn :pretzel:

This is my attempt at figuring out what I would like a
[seml](https://github.com/TUM-DAML/seml) equivalent built on top of
[hydra](https://hydra.cc) to look like. In particular, I want to have code isolation, i.e.
making a copy of the code when you run a job, so that you can continue working on your
code while your jobs wait in a SLURM queue.

`brezn` comes with *absolutely no guarantees* regarding stability or backwards
compatibility. You have been warned.

## Installation

You can install `brezn` from pypi (`pip install brezn`) though if you want the latest
version, you better install it straight from the repo.

```sh
pip install git+https://github.com/martenlienen/brezn
```

## Usage

### Configuration

You can configure `brezn` in a separate section of your `pyproject.toml`.

```toml
[tool.brezn]
# Directory that brezn should put its internal files and saved environments into
env_dir = ".brezn"
# Rules in the .gitignore format about which files should be included in the saved environments
files = [
  "brezn/**/*.py",
  "config/**/*.yaml",
]
```

### Run a command

`brezn run` creates a new copy of your code and then runs the command you provide from
there. Note that the working directory will be the directory where you issue `brezn run`.

```sh
brezn run ./train.py overrides=True
```