Update demo.ipynb

Author: JamshidJDMY

tests/demo.ipynb

@@ -315,7 +315,7 @@
         "from hinteval.evaluation.relevance import Rouge\n",
         "from hinteval.evaluation.readability import MachineLearningBased\n",
         "from hinteval.evaluation.convergence import LlmBased\n",
-        "from hinteval.evaluation.familiarity import Wikipedia\n",
+        "from hinteval.evaluation.familiarity import WordFrequency\n",
         "from hinteval.evaluation.answer_leakage import ContextualEmbeddings"
       ],
       "metadata": {
@@ -332,7 +332,7 @@
         "1. **Relevance (_Rouge_)**: Measures the relevance of the hints to the question using ROUGE-L algorithms.\n",
         "2. **Readability (_MachineLearningBased_)**: Uses a Random Forest algorithm to measure the readability of the hints and questions.\n",
         "3. **Convergence (_LLmBased_)**: Assesses how well the hints help eliminate incorrect answers using the Meta LLaMA-3.1-70b-Instruct-Turbo model.\n",
-        "4. **Familiarity (_Wikipedia_)**: Evaluates the familiarity of the information in the hints, questions, and answers based on Wikipedia view counts.\n",
+        "4. **Familiarity (_WordFrequency_)**: Evaluates the familiarity of the information in the hints, questions, and answers based on word occurancy.\n",
         "5. **AnswerLeakage (_ContextualEmbeddings_)**: Measures how much the hints reveal the answers by calculating the similarity between the hints and answers using contextual embeddings.\n",
         "\n",
         "To explore other metrics, check the [metrics guide](https://hinteval.readthedocs.io/en/latest/concepts/metrics/index.html)."
@@ -384,7 +384,7 @@
         "Rouge('rougeL', enable_tqdm=True).evaluate(instances)\n",
         "MachineLearningBased('random_forest', enable_tqdm=True).evaluate(questions + hints)\n",
         "LlmBased('llama-3-70b', together_ai_api_key=api_key, enable_tqdm=True).evaluate(instances)\n",
-        "Wikipedia(enable_tqdm=True).evaluate(questions + hints + answers)\n",
+        "WordFrequency(enable_tqdm=True).evaluate(questions + hints + answers)\n",
         "ContextualEmbeddings(enable_tqdm=True).evaluate(instances)\n",
         "pass"
       ],