Update README.md

README.md

@@ -17,4 +17,52 @@ library_name: pytorch
 This model was created as a part of the project for FI:PA228 (Masaryk University), 
 inspired by this paper: [Face Generation from Textual Features using Conditionally trained Inputs to Generative Adversarial Networks](https://arxiv.org/abs/2301.09123)
 
-It was trained on the generated dataset from BLIP and StyleGAN3.
+It was trained on the generated dataset from BLIP and StyleGAN3.
+
+## How to use
+
+
+```python
+import torch.nn as nn
+
+
+# for now, the model class needs to be defined, so...
+class LaTran(nn.Module):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.pipe = nn.Sequential(
+            nn.Conv1d(in_channels=1, out_channels=16, kernel_size=3, stride=1, padding=1),
+            nn.MaxPool1d(kernel_size=2, stride=2),
+            nn.Flatten(),
+            nn.Linear(3072, 512),
+            nn.ReLU(),
+            nn.Linear(512, 512)
+        )
+
+        # works but is big
+        self.pipe2 = nn.Sequential(
+            nn.Flatten(),
+            nn.Linear(384, 1024),
+            nn.ReLU(),
+            nn.Linear(1024, 512)
+        )
+
+        # works, and will be loaded
+        self.pipe3 = nn.Sequential(
+            nn.Flatten(),
+            nn.Linear(384, 512),
+            nn.ReLU(),
+            nn.Linear(512, 512)
+        )
+
+    def forward(self, v):
+        return self.pipe3(v.unsqueeze(1))
+
+
+
+# Instantiate and load the model
+dev = ...  # device to use
+PATH = "local_path_file_ending_like...sd.pt"
+model = LaTran().to(dev)
+model.load_state_dict(torch.load(TRANSLATION_MODEL, map_location=dev))
+```