Update README.md

README.md

@@ -56,10 +56,10 @@ passages = [
 # Load model and tokenizer
 tokenizer = AutoTokenizer.from_pretrained('Salesforce/SFR-Embedding-Mistral')
 model = AutoModel.from_pretrained('Salesforce/SFR-Embedding-Mistral')
-
+input_texts = [*queries, *passages]
 max_length = 4096
 # Tokenize the input texts
-batch_dict = tokenizer([*queries, *passages], max_length=max_length, padding=True, truncation=True, return_tensors="pt")
+batch_dict = tokenizer(input_texts, max_length=max_length, padding=True, truncation=True, return_tensors="pt")
 outputs = model(**batch_dict)
 embeddings = last_token_pool(outputs.last_hidden_state, batch_dict['attention_mask'])