zetascale 0.7.2

Transformers at zeta scales

Zeta - Seamlessly Create Zetascale Transformers

Create Ultra-Powerful Multi-Modality Models Seamlessly and Efficiently in as minimal lines of code as possible.

🤝 Schedule a 1-on-1 Session

Book a 1-on-1 Session with Kye, the Creator, to discuss any issues, provide feedback, or explore how we can improve Zeta for you.

Installation

To install:

pip install zetascale

To get hands-on and develop it locally:

git clone https://github.com/kyegomez/zeta.git
cd zeta
pip install -e .

Initiating Your Journey

Creating a model empowered with the aforementioned breakthrough research features is a breeze. Here's how to quickly materialize the renowned Flash Attention

import torch
from zeta import FlashAttention

q = torch.randn(2, 4, 6, 8)
k = torch.randn(2, 4, 10, 8)
v = torch.randn(2, 4, 10, 8)

attention = FlashAttention(causal=False, dropout=0.1, flash=True)
output = attention(q, k, v)

print(output.shape) 

Documentation

Click here for the documentation, it's at zeta.apac.ai

Vision

Zeta hopes to be the leading framework and library to effortlessly enable you to create the most capable and reliable foundation models out there with infinite scalability.

Acknowledgments

Zeta is a masterpiece inspired by LucidRains's repositories and elements of FairSeq and UniLM.

Contributing

We're dependent on you for contributions, it's only Kye maintaining this repository and it's very difficult and with that said any contribution is infinitely appreciated by not just me but by Zeta's users who dependen on this repository to build the world's best AI models

• Head over to the project board to look at open features to implement or bugs to tackle

Todo

• Head over to the project board to look at open features to implement or bugs to tackle

Project Board

This weeks iteration is here