TerraTorch：地理空间基础模型工具包
TerraTorch: The Geospatial Foundation Models Toolkit
AI总结：
TerraTorch是一个基于PyTorch Lightning的地理空间基础模型微调与基准测试工具包，支持无代码配置、自动化超参数优化，并与GEO-Bench集成，以降低新地球观测用例的模型开发门槛。
摘要：
TerraTorch是一个基于PyTorch Lightning构建的地理空间基础模型的微调与基准测试工具包，专为卫星、天气和气候数据设计。它集成了特定领域的数据模块、预定义任务以及一个模块化模型工厂，该工厂可将任何骨干网络与多种解码器头配对。这些组件使研究人员和实践者能够通过简单地编辑训练配置，以无代码方式微调支持的模型。通过整合模型开发的最佳实践并纳入自动化超参数优化扩展Iterate，TerraTorch降低了在新地球观测用例上微调或基准测试模型所需的专业知识和时间。此外，TerraTorch直接与GEO-Bench集成，支持对地理空间基础模型进行系统化和可复现的基准测试。TerraTorch在Apache 2.0许可下开源，可在https://github.com/IBM/terratorch获取，并可通过pip install terratorch安装。
英文摘要：
TerraTorch is a fine-tuning and benchmarking toolkit for Geospatial Foundation Models built on PyTorch Lightning and tailored for satellite, weather, and climate data. It integrates domain-specific data modules, pre-defined tasks, and a modular model factory that pairs any backbone with diverse decoder heads. These components allow researchers and practitioners to fine-tune supported models in a no-code fashion by simply editing a training configuration. By consolidating best practices for model development and incorporating the automated hyperparameter optimization extension Iterate, TerraTorch reduces the expertise and time required to fine-tune or benchmark models on new Earth Observation use cases. Furthermore, TerraTorch directly integrates with GEO-Bench, allowing for systematic and reproducible benchmarking of Geospatial Foundation Models. TerraTorch is open sourced under Apache 2.0, available at https://github.com/IBM/terratorch, and can be installed via pip install terratorch.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
