Update README.md

README.md

@@ -286,6 +286,7 @@ The successor of German_Semantic_STS_V2 is here!
 - **Matryoshka Embeddings:** The model is trained for embedding sizes from 1024 down to 64, allowing you to store much smaller embeddings with little quality loss.
 - **License:** Apache 2.0
 - **German only:** This model is German-only, causing the model to learn more efficient and deal better with shorter queries.
+- **Flexibility:** Trained with flexible sequence-length and embedding truncation, flexibility is a core feature of the model, while improving on V2-performance. 
 
 ## Usage:
 
@@ -296,7 +297,9 @@ from sentence_transformers import SentenceTransformer
 matryoshka_dim = 1024 # How big your embeddings should be, choose from: 64, 128, 256, 512, 1024
 model = SentenceTransformer("aari1995/German_Semantic_V3", trust_remote_code=True, truncate_dim=matryoshka_dim)
 
-#model.max_seq_length = 512 #optionally, set your maximum sequence length lower if your hardware is limited 
+# model.truncate_dim = 64 # truncation dimensions can also be changed after loading
+# model.max_seq_length = 512 #optionally, set your maximum sequence length lower if your hardware is limited 
+
 # Run inference
 sentences = [
     'Eine Flagge weht.',
@@ -307,6 +310,8 @@ embeddings = model.encode(sentences)
 
 # Get the similarity scores for the embeddings
 similarities = model.similarity(embeddings, embeddings)
+
+
 ```