AutoTrain：无代码训练最先进模型

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

October 21, 2024

作者: Abhishek Thakur

cs.AI

摘要

随着开源模型的进步，对自定义数据集进行训练（或微调）已成为开发针对特定工业或开源应用定制解决方案的关键部分。然而，目前尚无一种工具能简化跨不同类型模态或任务的训练过程。我们介绍了AutoTrain（又称AutoTrain Advanced）——一种开源、无代码工具/库，可用于训练（或微调）不同类型任务的模型，例如：大型语言模型（LLM）微调、文本分类/回归、标记分类、序列到序列任务、句子转换器微调、视觉语言模型（VLM）微调、图像分类/回归，甚至表格数据上的分类和回归任务。AutoTrain Advanced是一个提供在自定义数据集上训练模型的最佳实践的开源库。该库可在https://github.com/huggingface/autotrain-advanced 上找到。AutoTrain可在完全本地模式或云计算机上使用，并与Hugging Face Hub上共享的数以万计的模型及其变体配合使用。

English

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.