Update README.md

README.md

@@ -102,7 +102,7 @@ model = SentenceTransformer(
     model_kwargs={
         "torch_dtype": torch.bfloat16,
         "attn_implementation": "flash_attention_2",
-        "device_map": "auto"
+        "device_map": "cuda"
     }
 )
 
@@ -122,8 +122,8 @@ document_embeddings = model.encode(documents, prompt_name="nl2code_document")
 # Compute the (cosine) similarity between the query and document embeddings
 similarity = model.similarity(query_embeddings, document_embeddings)
 print(similarity)
-# tensor([[0.8157, 0.1222],
-#         [0.1201, 0.5500]])
+# tensor([[0.7650, 0.1131],
+#         [0.0938, 0.6607]])
 ```
 </details>