MambaByte
Implementation of MambaByte in "MambaByte: Token-free Selective State Space Model" in Pytorch and Zeta. Note this will be a higher performance implementation of Mamba with parallel scan
Installation
pip install mambabyte
Usage
import torch
from mambabyte import MambaConfig, Mamba
x = torch.randn(2, 3, 4)
config = MambaConfig(
dim = 4,
depth = 3,
dt_rank = 2,
d_state = 2,
expand_factor = 2,
d_conv = 3,
dt_min = 0.001,
dt_max = 0.1,
dt_init = "random",
dt_scale = 1.0,
bias = False,
conv_bias = True,
pscan = True
)
model = Mamba(config)
out = model(x)
print(out)
License
MIT
1 maintainer
Metadata
1 maintainer
Release files for mambabyte 0.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| mambabyte-0.0.2.tar.gz | 7.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mambabyte-0.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 14.0 kB
Release files / mambabyte-0.0.2.tar.gz
| Download URL | mambabyte-0.0.2.tar.gz |
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| Size | 7.0 kB |
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Release files / mambabyte-0.0.2-py3-none-any.whl
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| Size | 6.9 kB |
| Tags | Python 3 |
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