Metadata-Version: 2.1
Name: pali3
Version: 0.0.1
Summary: pali3 - Pytorch
Home-page: https://github.com/kyegomez/pali3
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: einops
Requires-Dist: torch
Project-URL: Repository, https://github.com/kyegomez/pali3
Description-Content-Type: text/markdown

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

# Pali3
![pali](pali.png)

"Figure 1: Overview of the PaLI-3 (5B) model: images are encoded into visual tokens individually
by the contrastively pretrained 2B SigLIP vision model. Along with a query, these visual tokens
are passed to an 3B encoder-decoder UL2 Transformer which produces the desired answer."



## Installation

`pip install pali3`


## Usage:



# License
MIT

# Todo

- [ ] Implement sig_lip vit model with training recipe
- [ ] Implement the text tokenizer, maybe use token monster 
- [ ] Implement the UL2 Transformer Encoder and Decoder
- [ ] Implement training scripts
- [ ] 
