[FEAT][AlphaFold3]

README.md

@@ -56,6 +56,37 @@ print(output_coords)
 print(loss)
 ```
 
+## Full Model Example Forward pass
+
+```python
+import torch 
+from alphafold3 import AlphaFold3
+
+# Create random tensors
+x = torch.randn(1, 5, 5, 64)  # Shape: (batch_size, seq_len, seq_len, dim)
+y = torch.randn(1, 5, 64)  # Shape: (batch_size, seq_len, dim)
+
+# Initialize AlphaFold3 model
+model = AlphaFold3(
+    dim=64,
+    seq_len=5,
+    heads=8,
+    dim_head=64,
+    attn_dropout=0.0,
+    ff_dropout=0.0,
+    global_column_attn=False,
+    pair_former_depth=48,
+    num_diffusion_steps=1000,
+    diffusion_depth=30,
+)
+
+# Forward pass through the model
+output = model(x, y)
+
+# Print the shape of the output tensor
+print(output.shape)
+```
+
 
 # Citation
 ```bibtex

model_example.py

@@ -1,9 +1,11 @@
 import torch 
 from alphafold3 import AlphaFold3
 
-x = torch.randn(1, 5, 5, 64)
-y = torch.randn(1, 5, 64)
+# Create random tensors
+x = torch.randn(1, 5, 5, 64)  # Shape: (batch_size, seq_len, seq_len, dim)
+y = torch.randn(1, 5, 64)  # Shape: (batch_size, seq_len, dim)
 
+# Initialize AlphaFold3 model
 model = AlphaFold3(
     dim=64,
     seq_len=5,
@@ -16,5 +18,9 @@
     num_diffusion_steps=1000,
     diffusion_depth=30,
 )
+
+# Forward pass through the model
 output = model(x, y)
+
+# Print the shape of the output tensor
 print(output.shape)

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "alphafold3"
-version = "0.0.1"
+version = "0.0.2"
 description = "Paper - Pytorch"
 license = "MIT"
 authors = ["Kye Gomez <kye@apac.ai>"]