NLP-docs | deep Learning/machine learning | Machine Learning library

by siat-nlp HTML Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | NLP-docs Summary

NLP-docs is a HTML library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow applications. NLP-docs has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Docs of NLP/deep Learning/machine learning, etc.

Support

Quality

Security

License

Reuse

Support

NLP-docs has a low active ecosystem.

It has 8 star(s) with 8 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

NLP-docs has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of NLP-docs is current.

Quality

NLP-docs has no bugs reported.

Security

NLP-docs has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

NLP-docs 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

NLP-docs releases are not available. You will need to build from source code and install.

Top functions reviewed by kandi - BETA

kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of NLP-docs

Get all kandi verified functions for this library.

NLP-docs Key Features

No Key Features are available at this moment for NLP-docs.

NLP-docs Examples and Code Snippets

No Code Snippets are available at this moment for NLP-docs.

Community Discussions

Trending Discussions on NLP-docs

Multi-GPU training of AllenNLP coreference resolution

QUESTION

Multi-GPU training of AllenNLP coreference resolution

Asked 2019-Aug-05 at 15:55

I'm trying to replicate (or come close) to the results obtained by the End-to-end Neural Coreference Resolution paper on the CoNLL-2012 shared task. I intend to do some enhancements on top of this, so I decided to use AllenNLP's CoreferenceResolver. This is how I'm initialising & training the model:

...

ANSWER

Answered 2019-Aug-05 at 15:55

After some digging through the code I found out that AllenNLP does this under the hood directly through its Trainer. The cuda_device can either be a single int (in the case of single-processing) or a list of ints (in the case of multi-processing):

cuda_device : Union[int, List[int]], optional (default = -1) An integer or list of integers specifying the CUDA device(s) to use. If -1, the CPU is used.

So all GPU devices needed should be passed on instead:

Source https://stackoverflow.com/questions/57277214

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

Vulnerabilities

No vulnerabilities reported

Install NLP-docs

You can download it from GitHub.

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 .

Find more information at: