From 2d507607c097632c6b1ab177912b906ed33784bf Mon Sep 17 00:00:00 2001
From: tian bao <2011xuesong@gmail.com>
Date: Thu, 6 Mar 2025 10:14:55 +0800
Subject: [PATCH] fix tope

---
 .../1_build_question_answering_engine.ipynb                 | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/nlp/question_answering/1_build_question_answering_engine.ipynb b/nlp/question_answering/1_build_question_answering_engine.ipynb
index c00d4c6..f4ecc6f 100644
--- a/nlp/question_answering/1_build_question_answering_engine.ipynb
+++ b/nlp/question_answering/1_build_question_answering_engine.ipynb
@@ -53,8 +53,8 @@
      "output_type": "stream",
      "text": [
       "\n",
-      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip available: \u001b[0m\u001b[31;49m22.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.0\u001b[0m\n",
-      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n"
+      "\u001B[1m[\u001B[0m\u001B[34;49mnotice\u001B[0m\u001B[1;39;49m]\u001B[0m\u001B[39;49m A new release of pip available: \u001B[0m\u001B[31;49m22.3.1\u001B[0m\u001B[39;49m -> \u001B[0m\u001B[32;49m23.0\u001B[0m\n",
+      "\u001B[1m[\u001B[0m\u001B[34;49mnotice\u001B[0m\u001B[1;39;49m]\u001B[0m\u001B[39;49m To update, run: \u001B[0m\u001B[32;49mpip install --upgrade pip\u001B[0m\n"
      ]
     }
    ],
@@ -394,7 +394,7 @@
     "\n",
     "`pipe.input('id', 'question', 'answer')`: Get three inputs, namely question's id, quesion's text and question's answer;\n",
     "\n",
-    "`map('question', 'vec', ops.text_embedding.dpr(model_name='facebook/dpr-ctx_encoder-single-nq-base'))`: Use the `acebook/dpr-ctx_encoder-single-nq-base` model to generate the question embedding vector with the [dpr operator](https://towhee.io/text-embedding/dpr) in towhee hub;\n",
+    "`map('question', 'vec', ops.text_embedding.dpr(model_name='facebook/dpr-ctx_encoder-single-nq-base'))`: Use the `facebook/dpr-ctx_encoder-single-nq-base` model to generate the question embedding vector with the [dpr operator](https://towhee.io/text-embedding/dpr) in towhee hub;\n",
     "\n",
     "`map('vec', 'vec', lambda x: x / np.linalg.norm(x, axis=0))`: normalize the embedding vector;\n",
     "\n",