model change

app.py

@@ -1,25 +1,23 @@
 # AUTOGENERATED! DO NOT EDIT! File to edit: ../drive/MyDrive/Codici/Python/Apps/Gradio_App/SemanticSearch_QA-v2.1.ipynb.
 
-# %% auto 0
+
 __all__ = ['model_name', 'qa_model', 'contexts', 'question', 'df_results', 'question_1', 'question_2', 'question_3', 'question_4',
            'question_5', 'question_6', 'question_7', 'question_8', 'question_9', 'question_10', 'title', 'description',
            'data', 'context_df', 'question_input', 'contexts_input', 'n_answers_input', 'full_context_input',
            'confidence_threshold_input', 'intf', 'get_answers']
 
-# %% ../drive/MyDrive/Codici/Python/Apps/Gradio_App/SemanticSearch_QA-v2.1.ipynb 2
 import pandas as pd
 import gradio as gr
 import transformers
 from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
 
-model_name = 'Francesco-A/bert-finetuned-squad-v1'
-# model_name = "deepset/roberta-base-squad2"
+# model_name = 'Francesco-A/bert-finetuned-squad-v1'
+model_name = "deepset/roberta-base-squad2"
 
 qa_model = pipeline(task = 'question-answering',
                     model = model_name,
                     tokenizer = model_name)
 
-# %% ../drive/MyDrive/Codici/Python/Apps/Gradio_App/SemanticSearch_QA-v2.1.ipynb 5
 def get_answers(question, contexts, n_answers=1, full_context=True, confidence_threshold = 0.5):
     results = []
 
@@ -30,7 +28,7 @@ def get_answers(question, contexts, n_answers=1, full_context=True, confidence_t
 
     for i, context in enumerate(contexts):
         QA_input = {'question': question, 'context': context}
-        res = qa_model(QA_input)
+        res = qa_model(question = QA_input['question'], context = QA_input['context'])
 
         results_dict = {
             'context_idx': i,
@@ -43,7 +41,7 @@ def get_answers(question, contexts, n_answers=1, full_context=True, confidence_t
           results_dict['Full Context'] = context
 
         results.append(results_dict)
-
+    
     df = pd.DataFrame(results)
     df = df[df['Score'] >= confidence_threshold]
     df = df.sort_values(by='Score', ascending=False).head(n_answers)
@@ -63,7 +61,6 @@ question = "Why is model conversion important?"
 df_results = get_answers(question,contexts,n_answers=2,full_context=False, confidence_threshold = 0.25)
 df_results
 
-# %% ../drive/MyDrive/Codici/Python/Apps/Gradio_App/SemanticSearch_QA-v2.1.ipynb 6
 # Define example question(s)
 question_1 = "What are the main features of the new XPhone 20?"
 question_2 = "What are some benefits of regular exercise?"
@@ -120,10 +117,9 @@ contexts = [
     "The Declaration of Independence was adopted by the Continental Congress on July 4, 1776.",
 ]
 
-# %% ../drive/MyDrive/Codici/Python/Apps/Gradio_App/SemanticSearch_QA-v2.1.ipynb 9
 title = 'SemanticSearch_QA-v2'
 description = """
-QA model: [Francesco-A/bert-finetuned-squad-v1](https://huggingface.co/Francesco-A/bert-finetuned-squad-v1)
+QA model: [deepset/roberta-base-squad2](https://huggingface.co/deepset/roberta-base-squad2)
 """
 
 data = {