Metadata-Version: 2.1
Name: cross-attn
Version: 0.0.2
Summary: MultiModalCrossAttn - Pytorch
Home-page: https://github.com/kyegomez/MultiModalCrossAttn
License: MIT
Keywords: artificial intelligence,deep learning,optimizers,Prompt Engineering
Author: Kye Gomez
Author-email: kye@apac.ai
Requires-Python: >=3.6,<4.0
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Dist: torch
Project-URL: Repository, https://github.com/kyegomez/MultiModalCrossAttn
Description-Content-Type: text/markdown

[![Multi-Modality](agorabanner.png)](https://discord.gg/qUtxnK2NMf)

# MultiModalCrossAttn
The open source implementation of the cross attention mechanism from the paper: "JOINTLY TRAINING LARGE AUTOREGRESSIVE MULTIMODAL MODELS"


[Paper Link](https://arxiv.org/pdf/2309.15564.pdf)

# Appreciation
* Lucidrains
* Agorians



# Install


# Usage

# Architecture

# Todo


# License
MIT

# Citations
```
@misc{2309.15564,
Author = {Emanuele Aiello and Lili Yu and Yixin Nie and Armen Aghajanyan and Barlas Oguz},
Title = {Jointly Training Large Autoregressive Multimodal Models},
Year = {2023},
Eprint = {arXiv:2309.15564},
}
```
