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Paper · arXiv 2410.15735

AutoTrain: No-code training for state-of-the-art models

Abhishek Thakur

59 upvotesOctober 21, 2024arXiv 预印本
AI 摘要

AutoTrain, an open-source tool, streamlines training and fine-tuning of various machine learning models across multiple tasks and modalities using best practices.

LLM finetuningtext classificationtoken classificationsequence-to-sequence tasksentence transformersVLM finetuningimage classificationtabular data classificationregression

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.

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