LW-PT | Wise Document Pre-Training for Multi-Label Text | Data Labeling library

 by   laddie132 Python Version: Current License: MIT

kandi X-RAY | LW-PT Summary

kandi X-RAY | LW-PT Summary

LW-PT is a Python library typically used in Artificial Intelligence, Data Labeling applications. LW-PT has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Dataset and code for "Label-Wise Document Pre-Training for Multi-Label Text Classification" (NLPCC 2020)
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              LW-PT has a low active ecosystem.
              It has 7 star(s) with 0 fork(s). There are 1 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              LW-PT has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of LW-PT is current.

            kandi-Quality Quality

              LW-PT has no bugs reported.

            kandi-Security Security

              LW-PT has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              LW-PT is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              LW-PT 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.

            Top functions reviewed by kandi - BETA

            kandi has reviewed LW-PT and discovered the below as its top functions. This is intended to give you an instant insight into LW-PT implemented functionality, and help decide if they suit your requirements.
            • Compute the word embedding
            • Compute the top layer mask
            • Train a model on a model
            • Evaluate f1
            • Evaluate the model on a given model
            • Evaluate hamming loss
            • Evaluate a single error
            • Update learning rate
            • Collect function labels from a batch
            • Removes zeros from a tensor
            • Compute the mask
            • Read configuration file
            • Evaluate a model on a given model
            • Forward layer attention
            • Collect docs and labels
            • Forward computation
            • Calculate softmax
            • Performs forward attention
            • Set the parameters
            • Generate a hierarchical sequence mask
            • Evaluate model on a model
            • Load weights from checkpoint file
            • Load weights from the model
            • Pretty print metrics
            • Load all training data
            • Updates the learning rate of the optimizer
            • Load all training data
            • Run preprocessors
            Get all kandi verified functions for this library.

            LW-PT Key Features

            No Key Features are available at this moment for LW-PT.

            LW-PT Examples and Code Snippets

            No Code Snippets are available at this moment for LW-PT.

            Community Discussions

            QUESTION

            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?

            ...

            ANSWER

            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

            QUESTION

            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:

            ...

            ANSWER

            Answered 2020-Nov-16 at 07:24

            QUESTION

            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.

            ...

            ANSWER

            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

            Vulnerabilities

            No vulnerabilities reported

            Install LW-PT

            You can download it from GitHub.
            You can use LW-PT 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.

            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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