Welcome to the FARM!

Framework for Adapting Representation Models

What is it?

FARM makes cutting edge Transfer Learning for NLP simple. Building upon transformers, FARM is a home for all species of pretrained language models (e.g. BERT) that can be adapted to different domain languages or down-stream tasks. With FARM you can easily create SOTA NLP models for tasks like document classification, NER or question answering. The standardized interfaces for language models and prediction heads allow flexible extension by researchers and easy application for practitioners. Additional experiment tracking and visualizations support you along the way to adapt a SOTA model to your own NLP problem and have a fast proof-of-concept.

Core features

  • Easy adaptation of language models (e.g. BERT) to your own use case

  • Fast integration of custom datasets via Processor class

  • Modular design of language model and prediction heads

  • Switch between heads or just combine them for multitask learning

  • Smooth upgrading to new language models

  • Powerful experiment tracking & execution

  • Simple deployment and visualization to showcase your model

Task

BERT

RoBERTa

XLNet

Text classification

x

x

x

NER

x

x

x

Question Answering

x

Language Model Fine-tuning

x

Text Regression

x

x

x

Multilabel Text classif.

x

x

x

Indices and tables