Skip to main content

MambaByte - Pytorch

Project description

Multi-Modality

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

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

mambabyte-0.0.2.tar.gz (7.0 kB view hashes)

Uploaded Source

Built Distribution

mambabyte-0.0.2-py3-none-any.whl (6.9 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