AutoTrain：無代碼訓練最先進模型

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

October 21, 2024

作者: Abhishek Thakur

cs.AI

摘要

隨著開源模型的進步，對自定義數據集進行模型訓練（或微調）已成為開發針對特定工業或開源應用的解決方案的重要部分。然而，目前尚無一個工具能簡化跨不同類型模態或任務的訓練過程。我們介紹 AutoTrain（又稱 AutoTrain Advanced）-- 一個開源的、無代碼工具/庫，可用於訓練（或微調）不同類型任務的模型，包括：大型語言模型（LLM）微調、文本分類/回歸、標記分類、序列到序列任務、句子轉換器微調、視覺語言模型（VLM）微調、圖像分類/回歸，甚至在表格數據上進行分類和回歸任務。AutoTrain Advanced 是一個提供在自定義數據集上訓練模型的最佳實踐的開源庫。該庫可在 https://github.com/huggingface/autotrain-advanced 上找到。AutoTrain 可以在完全本地模式或雲端機器上使用，並與 Hugging Face Hub 上共享的數以萬計的模型及其變體一起使用。

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.