[README]

README.md

@@ -9,6 +9,12 @@ A novel implementation of fusing ViT with Mamba into a fast, agile, and high per
 
 
 ## Usage
+
+### `MultiModalMambaBlock`
+- Basic Block with 1 pass through the vit and Mamba
+- Multiple fusion layers
+- Deep configuration
+
 ```python
 # Import the necessary libraries
 import torch 
@@ -41,6 +47,36 @@ print(out.shape)
 
 ```
 
+
+### `MMM`, Ready to use Model
+- MMM, Fully ready to train Multi-Modal Mamba Model
+
+```python
+import torch
+from mm_mamba.model import MMM
+
+x = torch.randint(0, 10000, (1, 224))
+img = torch.randn(1, 3, 224, 224)
+
+model = MMM(
+    vocab_size=10000,
+    dim=512,
+    depth=6,
+    dropout=0.1,
+    heads=8,
+    d_state=512,
+    image_size=224,
+    patch_size=16,
+    encoder_dim=512,
+    encoder_depth=6,
+    encoder_heads=8,
+    fusion_method="visual_expert",
+)
+
+out = model(x, img)
+print(out.shape)
+```
+
 # License
 MIT
 

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "mmm-zeta"
-version = "0.0.6"
+version = "0.0.7"
 description = "MMM - Pytorch"
 license = "MIT"
 authors = ["Kye Gomez <[email protected]>"]
@@ -27,11 +27,11 @@ packages = [
 
 [tool.poetry.dependencies]
 python = "^3.6"
-swarms = "*"
 torch = "2.1.2"
 zetascale = "1.4.0"
 
 
+
 [tool.poetry.group.lint.dependencies]
 ruff = "^0.1.6"
 types-toml = "^0.10.8.1"