Update README.md

README.md

@@ -98,6 +98,25 @@ AbstractPhil/gated-david/
 
 ### Loading the Model
 
+The description below is terrible.
+
+Load a clip-vit and then load one of the pretrains. There is no anchors file nor any of that anymore.
+
+I don't know why this piece of the readme got preserved, but I'll need to fix it.
+
+1. Install the repo in your environment
+
+```python
+try:
+  !pip uninstall -qy geometricvocab
+except:
+  pass
+
+!pip install -q git+https://github.com/AbstractEyes/lattice_vocabulary.git
+```
+
+Find your target model, likely not all of this below will work currently.
+
 ```python
 from geovocab2.train.model.core.david import David, DavidArchitectureConfig
 from huggingface_hub import hf_hub_download
@@ -135,23 +154,10 @@ david.load_state_dict(load_file(weights_path))
 david.eval()
 ```
 
-### Inference
-
-```python
-import torch
-import torch.nn.functional as F
-
-# Assuming you have CLIP features (512-dim for ViT-B/16)
-features = get_clip_features(image)  # [1, 512]
+3. When in eval mode pass the output from clip-vit's feature into david. The feature does not require the token nor the label, simply pass the feature in and assess the outputs.
 
-# Load anchors
-anchors_dict = torch.load("anchors.pth")
+  I'll need to ensure this process is perfected later, so the trainings can actually be utilized.
 
-# Forward pass
-with torch.no_grad():
-    logits, _ = david(features, anchors_dict)
-    predictions = logits.argmax(dim=-1)
-```
 
 ## Architecture Overview