Machine learning models from Singapore's NLP research community

Overview

SG-NLP

Machine learning models from Singapore's natural language processing (NLP) research community.

sgnlp is a Python package that allows you to easily get started on using various (NLP) models implemented using the Pytorch and Transfromers frameworks.

We have an accompanying demo site where you can interact with our models and get a better understanding on how they work.

Installation

  • Python >= 3.8
pip install sgnlp

Documentation

Visit our documentation for tutorials.

License

Code and models from this project are released under the MIT License unless otherwise stated. If a model's code is under a separate license, it can be found in the respective model's folder.

Comments
  • Change demo api to use gevent worker

    Change demo api to use gevent worker

    • Using multiple workers of the default type 'sync' in gunicorn is not working on Kubernetes
    • Workers constantly terminated due to signal 9
    • Try gevent to see if it works out
    opened by jonheng 2
  • UFD use case tutorial and usability improvement

    UFD use case tutorial and usability improvement

    • Added additional tutorial on how to use UFD to train and evaluate on custom dataset
    • Bug fix for UFD parse_args_and_load_config util function
    • Added feature to create folder if folder doesn't exist
    • Added some train args param in eval args param to improve usability
    • Made caching optional
    • Added validation to make debugging easier
    • Added links to config file examples for reccon models
    opened by vincenttzc 1
  • Wrong assert comparison for SenticGCN dataclass

    Wrong assert comparison for SenticGCN dataclass

    Latest SenticGCN implementation for the Dev branch. In the dataclass.py, post_init method in SenticGCNTrainArgs, there are the following assertions,

    assert self.repeats > 1, "Repeats value must be at least 1."
    assert self.patience > 1, "Patience value must be at least 1." 
    

    The comparison operator should be >= instead.

    bug 
    opened by raymondng76 0
  • 47 centralized logging

    47 centralized logging

    • Create a centralized logger for 'sgnlp' base logger
    • 'sgnlp' logger is created from a config json and is init a the 'sgnlp' module init.py
    • Replace all logging method call with their own script specific logger
    opened by raymondng76 0
  • Add parent class for preprocessor

    Add parent class for preprocessor

    • [x] Create a module named sgnlp.base
    • [x] Add abstractmethods for preprocess, save, load
    • [x] Add batch iteration to parent __call__
    • [x] Parent __call__ should return a dictionary
    enhancement 
    opened by jonheng 0
  • 46 senticgcn bugfix

    46 senticgcn bugfix

    • Add multi-word aspect support
    • Update documentation to reflect multi-word support
    • Update unit tests
    • Update usage example to include multi-word support
    opened by raymondng76 0
  • Fix multi-word aspect issue with Sentic-GCN preprocessor

    Fix multi-word aspect issue with Sentic-GCN preprocessor

    The current implementation of preprocessor matches a single aspect index for the purpose of matching postprocessor output. The aspect index field for process_input payload should be expended to handle aspects with multiple indexes.

    bug 
    opened by raymondng76 0
  • Add Sentic-GCN demo_api to SGNlp

    Add Sentic-GCN demo_api to SGNlp

    Close #43

    This pull request is to add Sentic-GCN demo_api models to sgnlp. Includes the follow components:

    • model_card
    • api.py
    • dockerfiles
    • requirements.txt
    • usage.py
    opened by K-WeiMing 0
  • Add Sentic-GCN to SGNlp

    Add Sentic-GCN to SGNlp

    close #41

    This pull request is to add Sentic-GCN models to sgnlp. Includes the follow components:

    • Models
    • Configs
    • Tokenizers
    • Embedding models
    • Trainer/Evaluator
    • Unit test
    • documentation

    Does not include demo_api as it is covered in another issue tickets.

    opened by raymondng76 0
  • download_pretrained for demo API does not cache downloaded files/models

    download_pretrained for demo API does not cache downloaded files/models

    To allow the containers to start up quicker, models and files were downloaded and cached during build time.

    Recent changes in the huggingface transformers package has broken this functionality:

    • Released in v4.22.0
    • Issue

    Possible choices moving forward:

    • Write a simple caching utility function
    • Stick to versions of transformers before 4.22.0
    opened by jonheng 0
  • Add Stance Detection model

    Add Stance Detection model

    opened by atenzer 0
Releases(v0.4.0)
Owner
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AI Singapore | AI Makerspace
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