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
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file configvlm-0.1.1.tar.gz
.
File metadata
- Download URL: configvlm-0.1.1.tar.gz
- Upload date:
- Size: 44.8 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.4.1 CPython/3.10.6 Linux/5.17.0-1028-oem
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8faca5c19e27c2f1117d45c5fde85158b3921f328ca6ffd295237015e4da8c46 |
|
MD5 | b387c7a54a6394cc7d1d84593ac9dc85 |
|
BLAKE2b-256 | 8ff889cd19f777402620793d3160aa50fe3634f430aa68bddc49f86b9d922d1c |
File details
Details for the file configvlm-0.1.1-py3-none-any.whl
.
File metadata
- Download URL: configvlm-0.1.1-py3-none-any.whl
- Upload date:
- Size: 44.9 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.4.1 CPython/3.10.6 Linux/5.17.0-1028-oem
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | a191cd9abd3211a10a37166aceeb2cb4fbba02dabd4c60de3ea3b57e0b592f1b |
|
MD5 | 3734d65bcbdcea3566ae7c8228039d90 |
|
BLAKE2b-256 | aba0f032d918b2ddd03a9e90a0224d82d58d5be859e3c8a82039051d8ddadaf8 |