wehub-resource-sync
133 lines
5.1 KiB
Markdown
133 lines
5.1 KiB
Markdown
# Install
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```{figure} _static/install-versions.svg
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---
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width: 100%
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figclass: caption
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alt: HanLP versions
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name: hanlp-versions
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---
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Choose your HanLP version
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```
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## Install RESTful Packages
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[](https://pepy.tech/project/hanlp-restful) [](https://pepy.tech/project/hanlp-restful) [](https://pepy.tech/project/hanlp-restful)
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```{eval-rst}
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.. margin:: **Beginners Attention**
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.. Hint:: New to NLP? Just install RESTful packages and call :meth:`~hanlp_restful.HanLPClient.parse` without pain.
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```
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For beginners, the recommended RESTful packages are easier to start with.
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The only requirement is [an auth key](https://bbs.hankcs.com/t/apply-for-free-hanlp-restful-apis/3178).
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We officially released the following language bindings:
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### Python
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```shell script
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pip install hanlp_restful
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```
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### Java
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See [Java instructions](https://hanlp.hankcs.com/docs/api/restful_java.html).
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### Golang
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See [Golang instructions](https://hanlp.hankcs.com/docs/api/restful_golang.html).
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## Install Native Package
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[](https://pepy.tech/project/hanlp) [](https://pepy.tech/project/hanlp) [](https://pepy.tech/project/hanlp)
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The native package running locally can be installed via pip.
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````{margin} **Install from Source**
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```{note}
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See [developer guideline](https://hanlp.hankcs.com/docs/contributing.html#development).
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```
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````
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```
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pip install hanlp
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```
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HanLP requires Python 3.6 or later. GPU/TPU is suggested but not mandatory. Depending on your preference, HanLP offers the following flavors:
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````{margin} **Windows Support**
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```{note}
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Installation on Windows is **perfectly** supported. No need to install Microsoft Visual C++ Build Tools anymore.
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```
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````
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````{margin} **Apple Silicon**
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```{note}
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HanLP also perfectly supports accelerating on Apple Silicon M1 chips, see [tutorial](https://www.hankcs.com/nlp/hanlp-official-m1-support.html).
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```
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````
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| Flavor | Description |
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| ------- | ------------------------------------------------------------ |
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| default | This installs the default version which delivers the most commonly used functionalities. However, some heavy dependencies like TensorFlow are not installed. |
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| tf | This installs TensorFlow and fastText. |
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| amr | To support Abstract Meaning Representation (AMR) models, this installs AMR related dependencies like `penman`. |
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| full | For experts who seek to maximize the efficiency via TensorFlow and C++ extensions, `pip install hanlp[full]` installs all the above dependencies. |
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## Install Models
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In short, you don't need to manually install any model. Instead, they are automatically downloaded to a directory called [`HANLP_HOME`](https://hanlp.hankcs.com/docs/configure.html#customize-hanlp-home) when you call `hanlp.load`.
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Occasionally, some errors might occur the first time you load a model, in which case you can refer to the following tips.
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### Download Error
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#### HanLP Models
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If the auto-download of a HanLP model fails, you can either:
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1. Retry as our file server might be busy serving users from all over the world.
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1. Follow the message on your terminal, which often guides you to manually download a `zip` file to a particular path.
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1. Use a [mirror site](https://hanlp.hankcs.com/docs/configure.html#use-mirror-sites) which could be faster and stabler in your region.
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#### Hugging Face 🤗 Transformers Models
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If the auto-download of a Hugging Face 🤗 Transformers model fails, e.g., the following exception is threw out:
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```bash
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lib/python3.8/site-packages/transformers/file_utils.py", line 2102, in get_from_cache
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raise ValueError(
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ValueError: Connection error, and we cannot find the requested files in the cached
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path. Please try again or make sure your Internet connection is on.
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```
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You can either:
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1. Retry as the Internet is quite unstable in some regions (e.g., China).
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2. Force Hugging Face 🤗 Transformers to use cached models instead of checking updates from the Internet **if you have ever successfully loaded it before**, by setting the following environment variable:
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```bash
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export TRANSFORMERS_OFFLINE=1
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```
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### Server without Internet
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If your server has no Internet access at all, just debug your codes on your local PC and copy the following directories to your server via a USB disk or something.
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1. `~/.hanlp`: the home directory for HanLP models.
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1. `~/.cache/huggingface`: the home directory for Hugging Face 🤗 Transformers.
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### Import Error
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Some TensorFlow/fastText models will ask you to install the missing TensorFlow/fastText modules, in which case you'll need to install the full version:
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```shell script
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pip install hanlp[full]
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```
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```{danger}
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NEVER install thirdparty packages (TensorFlow/fastText etc.) by yourself, as higher or lower versions of thirparty packages have not been tested and might not work properly.
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``` |