Update README.md

README.md

@@ -21,3 +21,29 @@ how to recontruction noicing image to cleaning image.
 LCVLM Train similiar Diffusion model when model training by self supervised learning by noiced image as input and clean image as output. 
 
 LCVLM Encoder train by Flickr8K datasets with MSE function as loss function, Adam as optimizers and here is model bechmark:
+
+![bechmark](./VLM2EncoderLoss.png)
+
+this bechmark train by spesific model:
+embedding_dim and d_model: 256 \n 
+Global_FFN: (1024,256) \n
+ConvTranspose2D: (128,64,64) \n
+num_LCT_block: 3 
+
+model_size: 8.6 mb \n 
+
+how to use mode:
+bash
+```
+    from  lctvlm import *
+    model =  PretrainedVIT(
+    image_size=224,
+    patch_size=8,
+    embdding_dim=256,
+    n_block=3
+    )
+    checkpoint = torch.load(path_model)
+    model.load_state_dict(checkpoint)
+```
+
+note: LCTVLM is still not finish to create, QFormers and LMLCT will update soon