A state-of-the-art tool for Python developers seeking to rapidly and iteratively develop vision and language models within the [`pytorch`](https://pytorch.org/) framework
Project description
ConfigVLM
The library ConfigVLM
is a state-of-the-art tool for Python developers seeking to rapidly and
iteratively develop vision and language models within the pytorch
framework.
This open-source library provides a convenient implementation for seamlessly combining models
from two of the most popular pytorch
libraries,
the highly regarded timm
and huggingface
🤗.
With an extensive collection of nearly 1000 vision and over 100 language models,
with an additional 120,000 community-uploaded models in the huggingface
🤗 model collection,
ConfigVLM
offers a diverse range of model combinations that require minimal implementation effort.
Its vast array of models makes it an unparalleled resource for developers seeking to create
innovative and sophisticated vision-language models with ease.
Furthermore, ConfigVLM
boasts a user-friendly interface that streamlines the exchange of model components,
thus providing endless possibilities for the creation of novel models.
Additionally, the package offers pre-built and throughput-optimized
pytorch dataloaders
and
lightning datamodules
,
which enable developers to seamlessly test their models in diverse application areas, such as Remote Sensing (RS).
Moreover, the comprehensive documentation of ConfigVLM
includes installation instructions,
tutorial examples, and a detailed overview of the framework's interface, ensuring a smooth and hassle-free development experience.
For detailed information please visit the publication or the documentation.
ConfigVLM
is released under the MIT Software License
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