🤗 AutoNLP

AutoNLP: Auto training and fast deployment for state-of-the-art NLP models

AutoNLP is an automatic way to train, evaluate and deploy state-of-the-art NLP models for different tasks. Using AutoNLP, you can leave all the worries of selecting the best model, fine-tuning the model or even deploying the models and focus on the broader picture for your project/business.

Main features:

  • Automatic selection of best models given your data

  • Automatic fine-tuning

  • Automatic hyperparameter optimization

  • Model comparison after training

  • Immediate deployment after training

  • CLI and Python API available

Supported Tasks

Currently, AutoNLP supports the following tasks:

  • Binary classification: one sentence has one target associated with it and there are two unique targets in the dataset

  • Multi-class classification: one sentence has one target associated with it and there are more than two unique targets in the dataset

  • Entity extraction: also known as named entity recognition or token classification. This task consists of one sentence and in the sentence, each token is associated to a particular label

  • Summarization: a sequence to sequence task in which the larger sequence is summarized to smaller sequence

  • Speech recognition: train your own automatic speech recognition model using AutoNLP

  • Single-column regression: train your own regression model

  • Extractive question answering: train custom question-answering models on your own dataset