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}
}
1 maintainer
Metadata
1 maintainer
Release files for vortex-fusion 0.0.2
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Source distribution (sdist)
| File | Size | Uploaded | |
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| vortex_fusion-0.0.2.tar.gz | 4.4 kB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| vortex_fusion-0.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 9.1 kB
Release files / vortex_fusion-0.0.2.tar.gz
| Download URL | vortex_fusion-0.0.2.tar.gz |
|---|---|
| Size | 4.4 kB |
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Release files / vortex_fusion-0.0.2-py3-none-any.whl
| Download URL | vortex_fusion-0.0.2-py3-none-any.whl |
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| Size | 4.7 kB |
| Tags | Python 3 |
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