Paper - Pytorch
Project description
Simba
A simpler Pytorch + Zeta Implementation of the paper: "SiMBA: Simplified Mamba-based Architecture for Vision and Multivariate Time series"
install
$ pip install simba-torch
usage
import torch
from simba_torch.main import Simba
# Forward pass with images
img = torch.randn(1, 3, 224, 224)
# Create model
model = Simba(
dim = 4, # Dimension of the transformer
dropout = 0.1, # Dropout rate for regularization
d_state=64, # Dimension of the transformer state
d_conv=64, # Dimension of the convolutional layers
num_classes=64, # Number of output classes
depth=8, # Number of transformer layers
patch_size=16, # Size of the image patches
image_size=224, # Size of the input image
channels=3, # Number of input channels
# use_pos_emb=True # If you want
)
# Forward pass
out = model(img)
print(out.shape)
License
MIT
Todo
- Add paper link
- Add citation bibtex
- cleanup
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