FewShotMultiLabel | AAAI2021 paper : Few-Shot Learning | Data Labeling library

 by   AtmaHou Python Version: Current License: No License

kandi X-RAY | FewShotMultiLabel Summary

kandi X-RAY | FewShotMultiLabel Summary

FewShotMultiLabel is a Python library typically used in Artificial Intelligence, Data Labeling, Deep Learning, Pytorch applications. FewShotMultiLabel has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

Code for AAAI2021 paper: Few-Shot Learning for Multi-label Intent Detection.

            kandi-support Support

              FewShotMultiLabel has a low active ecosystem.
              It has 52 star(s) with 13 fork(s). There are 4 watchers for this library.
              It had no major release in the last 6 months.
              There are 0 open issues and 5 have been closed. On average issues are closed in 3 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of FewShotMultiLabel is current.

            kandi-Quality Quality

              FewShotMultiLabel has 0 bugs and 0 code smells.

            kandi-Security Security

              FewShotMultiLabel has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              FewShotMultiLabel code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              FewShotMultiLabel does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
              Without a license, all rights are reserved, and you cannot use the library in your applications.

            kandi-Reuse Reuse

              FewShotMultiLabel releases are not available. You will need to build from source code and install.
              Build file is available. You can build the component from source.
              Installation instructions are not available. Examples and code snippets are available.
              FewShotMultiLabel saves you 3239 person hours of effort in developing the same functionality from scratch.
              It has 6961 lines of code, 467 functions and 50 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed FewShotMultiLabel and discovered the below as its top functions. This is intended to give you an instant insight into FewShotMultiLabel implemented functionality, and help decide if they suit your requirements.
            • Forward computation
            • Remove a tensor from a tensor
            • Build the context embedding
            • Check if a transition is allowed
            • Return a list of allowed transitions
            • Load embedding
            • Train the model
            • Make a check point
            • Returns a sampler instance
            • Split all domains into domains
            • Dump data to a directory
            • Loads data from files
            • Calculate MLC support
            • Generate example data
            • Load SMP data
            • Generate data for similarity method
            • Prepare optimizer
            • Make preprocessor
            • Load data from DSTC4 tour
            • Compute the similarity between examples
            • Concatenate examples
            • Generate data
            • Get tag data
            • Forward computation
            • Split eval_set with labels
            • Check if options are valid
            Get all kandi verified functions for this library.

            FewShotMultiLabel Key Features

            No Key Features are available at this moment for FewShotMultiLabel.

            FewShotMultiLabel Examples and Code Snippets

            No Code Snippets are available at this moment for FewShotMultiLabel.

            Community Discussions


            How can I do this split process in Python?
            Asked 2021-Dec-30 at 14:06

            I'm trying to make a data labeling in a table, and I need to do it in such a way that, in each row, the index is repeated, however, that in each column there is another Enum class.

            What I've done so far is make this representation with the same enumerator class.

            A solution using the column separately as a list would also be possible. But what would be the best way to resolve this?



            Answered 2021-Dec-30 at 13:57

            Instead of using Enum you can use a dict mapping. You can avoid loops if you flatten your dataframe:

            Source https://stackoverflow.com/questions/70532286


            Replacing a character with a space and dividing the string into two words in R
            Asked 2020-Nov-18 at 07:32

            I have a dataframe that contains a column that includes strings separeted with semi-colons and it is followed by a space. But unfortunately in some of the strings there is a semi-colon that is not followed by a space.

            In this case, This is what i'd like to do: If there is a space after the semi-colon we do not need a change. However if there are letters before and after the semi-colon, we should change semi-colon with space

            i have this:



            Answered 2020-Nov-16 at 07:24


            Azure ML FileDataset registers, but cannot be accessed for Data Labeling project
            Asked 2020-Oct-28 at 20:31

            Objective: Generate a down-sampled FileDataset using random sampling from a larger FileDataset to be used in a Data Labeling project.

            Details: I have a large FileDataset containing millions of images. Each filename contains details about the 'section' it was taken from. A section may contain thousands of images. I want to randomly select a specific number of sections and all the images associated with those sections. Then register the sample as a new dataset.

            Please note that the code below is not a direct copy and paste as there are elements such as filepaths and variables that have been renamed for confidentiality reasons.



            Answered 2020-Oct-27 at 22:39

            Is the data behind virtual network by any chance?

            Source https://stackoverflow.com/questions/64546521

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


            No vulnerabilities reported

            Install FewShotMultiLabel

            You can download it from GitHub.
            You can use FewShotMultiLabel like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.


            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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