sacremoses | Python port of Moses tokenizer , truecaser and normalizer | Natural Language Processing library

by alvations Python Version: 0.0.53 License: MIT

X-Ray Key Features Code Snippets Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | sacremoses Summary

sacremoses is a Python library typically used in Artificial Intelligence, Natural Language Processing, Bert applications. sacremoses has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. However sacremoses has 2 bugs. You can install using 'pip install sacremoses' or download it from GitHub, PyPI.

Python port of Moses tokenizer, truecaser and normalizer

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Quality

Security

License

Reuse

Support

sacremoses has a low active ecosystem.

It has 459 star(s) with 51 fork(s). There are 10 watchers for this library.

It had no major release in the last 12 months.

There are 27 open issues and 50 have been closed. On average issues are closed in 88 days. There are 6 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of sacremoses is 0.0.53

Quality

sacremoses has 2 bugs (1 blocker, 0 critical, 1 major, 0 minor) and 69 code smells.

Security

sacremoses has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

sacremoses code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

sacremoses is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

sacremoses releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

sacremoses saves you 956 person hours of effort in developing the same functionality from scratch.

It has 2363 lines of code, 99 functions and 20 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed sacremoses and discovered the below as its top functions. This is intended to give you an instant insight into sacremoses implemented functionality, and help decide if they suit your requirements.

Train a model from a file - like object
Train the model
Convert a casing to a dict
Save a model from a given casing
Learn each symbol
Replaces the pair with the given pair
Modify a token
Updates statistics for a pair
Yields truecased tokens from a file
Split a line into tokens
Compute the truecaser sentence
Tokenize a file
Apply func to each line
Parallelize a pre - process function
Calculate pairwise pair frequencies
Combine two iterables
Load model from file
Splits an iterable
Tokenize text
Check for nonbreaking prefixes
Detokenize a file
Train a truecaser model
Parse a MosesDetrue file
Attempt to train a model on a given file
Normalize a file
Compute the true case weights for each token

Get all kandi verified functions for this library.

sacremoses Key Features

No Key Features are available at this moment for sacremoses.

sacremoses Examples and Code Snippets

No Code Snippets are available at this moment for sacremoses.

Community Discussions

Trending Discussions on sacremoses

Using sentence transformers with limited access to internet

ModuleNotFoundError: No module named 'nn_pruning.modules.quantization'

HuggingFace - 'optimum' ModuleNotFoundError

ModuleNotFoundError: No module named 'h5py.utils'

python packages not being installed on the virtual environment using ubuntu

Heroku: Compiled Slug Size is too large Python

Why doesn't `conda env export` list all pip packages?

pip getting killed in Docker

torch.nn.CrossEntropyLoss().ignore_index is crashing when importing transfomers library

How to speed up the 'Adding visible gpu devices' process in tensorflow with a 30 series card?

QUESTION

Using sentence transformers with limited access to internet

Asked 2022-Jan-19 at 13:27

I have access to the latest packages but I cannot access internet from my python enviroment.

Package versions that I have are as below

...

ANSWER

Answered 2022-Jan-19 at 13:27

Based on the things you mentioned, I checked the source code of sentence-transformers on Google Colab. After running the model and getting the files, I check the directory and I saw the pytorch_model.bin there.

And according to sentence-transformers code: Link

the flax_model.msgpack , rust_model.ot, tf_model.h5 are getting ignored when the it is trying to download.

and these are the files that it downloads :

Source https://stackoverflow.com/questions/70716702

QUESTION

ModuleNotFoundError: No module named 'nn_pruning.modules.quantization'

Asked 2022-Jan-14 at 10:46

Goal: install nn_pruning.

Kernel: conda_pytorch_p36. I performed Restart & Run All.

It seems to recognise the optimize_model import, but not other functions. Even though they are from the same nn_pruning library.

...

ANSWER

Answered 2022-Jan-14 at 10:46

An Issue has since been approved to amend this.

Source https://stackoverflow.com/questions/70621833

QUESTION

HuggingFace - 'optimum' ModuleNotFoundError

Asked 2022-Jan-11 at 12:49

I want to run the 3 code snippets from this webpage.

I've made all 3 one post, as I am assuming it all stems from the same problem of optimum not having been imported correctly?

Kernel: conda_pytorch_p36

Installations:

...

ANSWER

Answered 2022-Jan-11 at 12:49

Pointed out by a Contributor of HuggingFace, on this Git Issue,

The library previously named LPOT has been renamed to Intel Neural Compressor (INC), which resulted in a change in the name of our subpackage from lpot to neural_compressor. The correct way to import would now be from optimum.intel.neural_compressor.quantization import IncQuantizerForSequenceClassification Concerning the graphcore subpackage, you need to install it first with pip install optimum[graphcore] Furthermore you'll need to have access to an IPU in order to use it.

Solution

Source https://stackoverflow.com/questions/70607224

QUESTION

ModuleNotFoundError: No module named 'h5py.utils'

Asked 2021-Dec-03 at 05:11

So I am trying to run a chat-bot which I built using Tkinter and transformers as a standalone exe file [I am using Windows 10] but I would get a run time error every-time I execute it. Is there something I am doing wrong? I have been trying different commands for nearly 2 days.

Error generated below:

...

ANSWER

Answered 2021-Dec-03 at 05:11

I solved my problem. Here's what I did

Before I start, do not use -onefile flag in your command.

I ran the command " pyinstaller -w --icon=logo.ico --hidden-import="h5py.defs" --hidden-import="h5py.utils" --hidden-import="h5py.h5ac" --hidden-import="h5py._proxy" --hidden-import=tensorflow --hidden-import=transformers --hidden-import=tqdm --collect-data tensorflow --collect-data torch --copy-metadata tensorflow --copy-metadata torch --copy-metadata h5py --copy-metadata tqdm --copy-metadata regex --copy-metadata sacremoses --copy-metadata requests --copy-metadata packaging --copy-metadata filelock --copy-metadata numpy --copy-metadata tokenizers --copy-metadata importlib_metadata chatbot.py "
Go to the \Lib\site-packages\certifi folder and copy the cacert.prem file.
When you try to run the exe file from the generated dist folder, you will get an OSError about a missing TLS CA certificate bundle because it's pointing to a certifi folder that does not exist within the dist folder. From the generated dist folder, go to the main folder, Create a new folder and rename it "certifi" and paste the cacert.prem file in it.
Re-run your exe file and it should work, it worked for me.

Source https://stackoverflow.com/questions/70205979

QUESTION

python packages not being installed on the virtual environment using ubuntu

Asked 2021-Aug-18 at 18:11

I have a requirements.txt file which holds all information of my python packages I need for my Flask application. Here is what I did:

python3 -m venv venv
source venv/bin/activate
sudo pip install -r requirements.txt

When I tried to check if the packages were installed on the virtual environment using pip list, I do not see the packages. Can someone tell what went wrong?

...

ANSWER

Answered 2021-Aug-18 at 18:05

If you want to use python3+ to install the packages try to use pip3 install package_name

And to solve the errno 13 try to add --user at the end

Source https://stackoverflow.com/questions/68837021

QUESTION

Heroku: Compiled Slug Size is too large Python

Asked 2021-Jul-21 at 06:50

I trying to deploy my app to heroku

I have following deploying error

...

ANSWER

Answered 2021-Jul-21 at 06:50

The maximum allowed slug size is 500MB. Slugs are an important aspect for heroku. When you git push to Heroku, your code is received by the slug compiler which transforms your repository into a slug.

First of all, lets determine what all files are taking up a considerate amount of space in your slug. To do that, fire up your heroku cli and enter / access your dyno by typing the following:

Source https://stackoverflow.com/questions/68464527

QUESTION

Why doesn't `conda env export` list all pip packages?

Asked 2021-Mar-28 at 09:18

To list all of the packages in my active environment in a format that resembles pip freeze:

...

ANSWER

Answered 2021-Mar-28 at 09:05

conda only keeps track of the packages it installed
pip freeze will give you the packages that were either installed using pip package manager or they used setuptools in their setup.py so conda build generated the egg information.

conda vs pip

Downgrading the pip may fix this issue, you can check this out: conda issues

Source https://stackoverflow.com/questions/66839700

QUESTION

pip getting killed in Docker

Asked 2021-Feb-22 at 06:09

I am building a Docker container based on python:3.7-slim-stretch (same problem also happens on python:3.7-slim-stretch), and it is getting Killed on

...

ANSWER

Answered 2021-Feb-22 at 06:09

I experience something similar on Windows when my docker containers run out of memory in WSL. I think the settings are different for Mac, but it looks like there is info here on setting the VM RAM/disk size/swap file settings for Docker for Desktop on Mac:

https://docs.docker.com/docker-for-mac

Source https://stackoverflow.com/questions/66258967

QUESTION

torch.nn.CrossEntropyLoss().ignore_index is crashing when importing transfomers library

Asked 2021-Jan-28 at 09:25

I am using layoutlm github which require python 3.6, transformer 2.9.0. I created an conda env:

...

ANSWER

Answered 2021-Jan-28 at 09:25

It seems something was broken on layoutlm with pytorch 1.4 related issue. Switching to pytorch 1.6 fix the issue with the core dump, and the layoutlm code run without any modification.

Source https://stackoverflow.com/questions/65582498

QUESTION

How to speed up the 'Adding visible gpu devices' process in tensorflow with a 30 series card?

Asked 2021-Jan-03 at 00:37

I get stuck with that for ~2 minute every time I run the code. Many people on the Internet said that it would only take a long time in the first run, but that's not my case. Although it doesn't make anything go wrong, it's pretty annoying. When I'm stuck, the system is under pretty low usage, including the CPU, system RAM, GPU, video memory. I'm using Nvidia Geforce RTX 3070, Windows 10 x64 20H2.Here's my environment:

...

ANSWER

Answered 2021-Jan-03 at 00:37

Just go to Windows Environment Variables and set CUDA_CACHE_MAXSIZE=2147483648 under system variables. And you need a REBOOT,then everything will be fine.

You are lucky enough to get an Ampere card, since they're out of stock everywhere.

Source https://stackoverflow.com/questions/65542317

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install sacremoses

NOTE: Sacremoses only supports Python 3 now (sacremoses>=0.0.41). If you're using Python 2, the last possible version is sacremoses==0.0.40.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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