Question-Answering-System | Question Answering System | Machine Learning library

by vaibhavs4424 Java Version: Current License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | Question-Answering-System Summary

Question-Answering-System is a Java library typically used in Institutions, Learning, Education, Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. Question-Answering-System has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However Question-Answering-System build file is not available. You can download it from GitHub.

Question Answering System Based on Artificial Intelligence for Restricted Domain: The project aims at an intelligent learning system that will take a text file as an input and extracts knowledge from the given text. Thus using this knowledge our system will try to answer questions fired to it by the user. Question Answering(QA) systems are designed to find answers to open domain questions in a documents. The main goal of the Question Answering system is to encourage research into systems that return answers because many users prefer direct answers, and bring benefits of large-scale evaluation to QA task. In its own form, the project could be used in online assessment of FAQs in different fields and also for interactive online lectures.

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Support

Question-Answering-System has a low active ecosystem.

It has 4 star(s) with 2 fork(s). There are no watchers for this library.

It had no major release in the last 6 months.

Question-Answering-System has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Question-Answering-System is current.

Quality

Question-Answering-System has 0 bugs and 0 code smells.

Security

Question-Answering-System has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Question-Answering-System code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Question-Answering-System is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

Question-Answering-System releases are not available. You will need to build from source code and install.

Question-Answering-System has no build file. You will be need to create the build yourself to build the component from source.

It has 1639 lines of code, 4 functions and 1 files.

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

Top functions reviewed by kandi - BETA

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

Demonstrates how to enter a questionnaire
Compare 2 words in the query
Demonstrates how to explain how to use a few words
Ask for user to enter a user input

Get all kandi verified functions for this library.

Question-Answering-System Key Features

No Key Features are available at this moment for Question-Answering-System.

Question-Answering-System Examples and Code Snippets

No Code Snippets are available at this moment for Question-Answering-System.

Community Discussions

Trending Discussions on Question-Answering-System

Type errors with BERT example

No such file or directory Error with Google Cloud Storage

QUESTION

Type errors with BERT example

Asked 2021-Aug-21 at 07:45

I'm new to BERT QA model & was trying to follow the example found in this article. The problem is when I run the code attached to the example it produces a Type error as follows TypeError: argmax(): argument 'input' (position 1) must be Tensor, not str.

Here is the code that I've tried running :

...

ANSWER

Answered 2021-Aug-21 at 07:45

So after referring to the BERT Documentation we identified that the model output object contains multiple properties not only start & end scores. Thus, we applied the following changes to the code.

Source https://stackoverflow.com/questions/68870383

QUESTION

No such file or directory Error with Google Cloud Storage

Asked 2020-Aug-27 at 01:21

I quite new to Google Cloud Platform and I am trying to train a model with TPU. I follow this tutorial to set up the TPU with Google Colab. All the code below follows the tutorial.

This is the step I have done:

...

ANSWER

Answered 2020-Aug-08 at 04:12

Can you post the part where run_coqa.py is opening the file?

It seems like you're trying to open it with a regular os. command where you should be using GCP's sdk.

Source https://stackoverflow.com/questions/63311656

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

Vulnerabilities

No vulnerabilities reported

Install Question-Answering-System

You can download it from GitHub.
You can use Question-Answering-System like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the Question-Answering-System component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

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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