Skip to main content

Paper - Pytorch

Project description

Multi-Modality

Vortex Fusion

This is the first ever implementation of a joint Transformer + Mamba + LSTM architecture. The flow is the following: mamba -> transformer -> lstm in a loop. Perhaps with more iteration on model design, we can find a better architecture but this architecture is the future.

install

$ pip3 install -U vortex-fusion

Usage

import torch
from vortex_fusion import VortexFusion

# Generate random input tensor
x = torch.randint(0, 10000, (1, 10))

# Create an instance of the VortexFusion model with dimension 512
model = VortexFusion(dim=512)

# Pass the input tensor through the model to get the output
output = model(x)

# Print the shape of the output tensor
print(output.shape)

License

MIT

Citation

Please cite Swarms in your paper or your project if you found it beneficial in any way! Appreciate you.

@misc{swarms,
  author = {Gomez, Kye},
  title = {{Swarms: The Multi-Agent Collaboration Framework}},
  howpublished = {\url{https://github.com/kyegomez/swarms}},
  year = {2023},
  note = {Accessed: Date}
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

vortex_fusion-0.0.2.tar.gz (4.4 kB view hashes)

Uploaded Source

Built Distribution

vortex_fusion-0.0.2-py3-none-any.whl (4.7 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page