AutoTrain: No-code training for state-of-the-art models
Abhishek Thakur
2024-10-22
Summary
This paper introduces AutoTrain, an open-source tool that allows users to train advanced machine learning models without needing to write any code.
What's the problem?
Training machine learning models, especially on custom datasets, can be complex and time-consuming. Many existing tools are not user-friendly and require coding skills, making it hard for people without technical backgrounds to develop tailored solutions for specific tasks like text or image classification.
What's the solution?
To solve this problem, the authors created AutoTrain, which simplifies the training process for various types of tasks, including large language model fine-tuning, image classification, and more. It provides a no-code interface that allows users to easily configure their projects, process datasets, and train models efficiently. AutoTrain also supports both local and cloud-based training, making it accessible to a wider audience.
Why it matters?
This research is important because it democratizes access to advanced machine learning technologies. By making it easier for anyone—regardless of their technical skills—to train sophisticated models, AutoTrain can help accelerate innovation in fields like artificial intelligence and data science. This could lead to more diverse applications and solutions tailored to specific needs in various industries.
Abstract
With the advancements in open-source models, training (or finetuning) models on custom datasets has become a crucial part of developing solutions which are tailored to specific industrial or open-source applications. Yet, there is no single tool which simplifies the process of training across different types of modalities or tasks. We introduce AutoTrain (aka AutoTrain Advanced) -- an open-source, no code tool/library which can be used to train (or finetune) models for different kinds of tasks such as: large language model (LLM) finetuning, text classification/regression, token classification, sequence-to-sequence task, finetuning of sentence transformers, visual language model (VLM) finetuning, image classification/regression and even classification and regression tasks on tabular data. AutoTrain Advanced is an open-source library providing best practices for training models on custom datasets. The library is available at https://github.com/huggingface/autotrain-advanced. AutoTrain can be used in fully local mode or on cloud machines and works with tens of thousands of models shared on Hugging Face Hub and their variations.