lxmert | PyTorch code for EMNLP 2019 paper | Machine Learning library

by airsplay Python Version: Current License: MIT

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

kandi X-RAY | lxmert Summary

lxmert is a Python library typically used in Artificial Intelligence, Machine Learning, Pytorch applications. lxmert 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.

PyTorch code for the EMNLP 2019 paper "LXMERT: Learning Cross-Modality Encoder Representations from Transformers". Slides of our EMNLP 2019 talk are avialable here.

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Quality

Security

License

Reuse

Support

lxmert has a low active ecosystem.

It has 674 star(s) with 114 fork(s). There are 18 watchers for this library.

It had no major release in the last 6 months.

There are 44 open issues and 56 have been closed. On average issues are closed in 9 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of lxmert is current.

Quality

lxmert has 0 bugs and 0 code smells.

Security

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

lxmert code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

lxmert 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

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

Load a pretrained model from a pretrained model
Download a file from the cache
Return a cached file path
Download a file via http
Load QA pre - trained LXRT
Convert ANSI ANSI ANSI ANSI ANS
Parse command line options
Get the optimizer
Compute the BERT prediction
Train the model
Evaluate the training epoch
Performs validation on a batch
Tokenize text
Create a vocabulary from a pretrained model
Compute the attention matrix
Generate a tsv from a tsv file
Loads the list of images
Evaluate the model
Run the forward computation
Construct a dataset from the given splits
Load GQEA data
Perform the forward computation
Get a data tuple from splits
Loads the model
Evaluate the prediction
Load model from file

Get all kandi verified functions for this library.

lxmert Key Features

No Key Features are available at this moment for lxmert.

lxmert Examples and Code Snippets

No Code Snippets are available at this moment for lxmert.

Community Discussions

Trending Discussions on lxmert

ValueError: Unrecognized model in ./MRPC/. Should have a `model_type` key in its config.json, or contain one of the following strings in its name

QUESTION

ValueError: Unrecognized model in ./MRPC/. Should have a `model_type` key in its config.json, or contain one of the following strings in its name

Asked 2022-Jan-13 at 14:10

Goal: Amend this Notebook to work with Albert and Distilbert models

Kernel: conda_pytorch_p36. I did Restart & Run All, and refreshed file view in working directory.

Error occurs in Section 1.2, only for these 2 new models.

For filenames etc., I've created a variable used everywhere:

...

ANSWER

Answered 2022-Jan-13 at 14:10

Explanation:

When instantiating AutoModel, you must specify a model_type parameter in ./MRPC/config.json file (downloaded during Notebook runtime).

List of model_types can be found here.

Solution:

Code that appends model_type to config.json, in the same format:

Source https://stackoverflow.com/questions/70697470

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

Vulnerabilities

No vulnerabilities reported

Install lxmert

You can download it from GitHub.
You can use lxmert 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

All default download links are provided by our servers in UNC CS department and under our NLP group website but the network bandwidth might be limited. We thus provide a few other options with Google Drive and Baidu Drive.

Find more information at: