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@@ -8885,6 +8885,8 @@ embeddings_1 = model.encode_queries(queries)
 embeddings_2 = model.encode_corpus(documents)
 similarity = embeddings_1 @ embeddings_2.T
 print(similarity)
+# [[ 0.559     0.01654 ]
+# [-0.002575  0.4998  ]]
 ```
 
 By default, FlagLLMModel will use all available GPUs when encoding. Please set `os.environ["CUDA_VISIBLE_DEVICES"]` to select specific GPUs.
@@ -8943,6 +8945,7 @@ with torch.no_grad():
 embeddings = F.normalize(embeddings, p=2, dim=1)
 scores = (embeddings[:2] @ embeddings[2:].T) * 100
 print(scores.tolist())
+# [[55.92064666748047, 1.6549524068832397], [-0.2698777914047241, 49.95653533935547]]
 ```