kandi X-RAY | lm-finetuning Summary
kandi X-RAY | lm-finetuning Summary
lm-finetuning is a Python library. lm-finetuning 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.
lm-finetuning
lm-finetuning
Support
Quality
Security
License
Reuse
Support
lm-finetuning has a low active ecosystem.
It has 5 star(s) with 1 fork(s). There are 1 watchers for this library.
It had no major release in the last 6 months.
lm-finetuning has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of lm-finetuning is current.
Quality
lm-finetuning has no bugs reported.
Security
lm-finetuning has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
lm-finetuning 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
lm-finetuning 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.
Top functions reviewed by kandi - BETA
kandi has reviewed lm-finetuning and discovered the below as its top functions. This is intended to give you an instant insight into lm-finetuning implemented functionality, and help decide if they suit your requirements.
- Train discriminator
- Calculate the average representation
- Train the model with the given arguments
- Get a data loader for the given dataset and discriminator
- Evaluate performance of the given discriminator
- Runs a pretrained model
- Build one - hot bow bow vectors
- Full text generation function
- Generate text plm
- Tokenize text
- Tokenize wikitext
- Tokenize a list of files
- Compute the loss of a batch
- Initialize an instance of WarmUp
- Default learning rate
- Helper function for resource_apply
- Wrapper for resource_apply
- Train the model
- Performs a training step
- Compute the logits of the classifier
- Create the vars for each variable
- Run a trained model
- Generate IMDB files
- Load a dataset from disk
- Tokenize files
- Evaluate the model
- Evaluate the loss function
Get all kandi verified functions for this library.
lm-finetuning Key Features
No Key Features are available at this moment for lm-finetuning.
lm-finetuning Examples and Code Snippets
No Code Snippets are available at this moment for lm-finetuning.
Community Discussions
No Community Discussions are available at this moment for lm-finetuning.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install lm-finetuning
You can download it from GitHub.
You can use lm-finetuning 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.
You can use lm-finetuning 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 .
Find more information at:
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page
