Update README.md

README.md

@@ -33,21 +33,18 @@ Multilingual embedding model (Kazakh/Russian/English) fine-tuned from `BAAI/bge-
 
 ## Usage
 
-Local model usage:
+### Direct model usage (Hugging Face)
 ```python
 from sentence_transformers import SentenceTransformer
 
-model = SentenceTransformer("./outputs/embedding-model")
+model = SentenceTransformer("Darmm/darmm-embedding-multilingual")
 sentences = ["Darmm қызметтері қандай?", "What services does Darmm provide?"]
 embeddings = model.encode(sentences)
 print(embeddings.shape)
 ```
 
-If published to Hugging Face, replace the path with your repo id.
-
 ## Training data (verified)
 - Darmm landing, academy, and mentor site text extracted from local sources.
-Local model usage:
 
 ## Training setup
 - Base model: `BAAI/bge-m3`.