Update app.py

app.py

@@ -150,19 +150,19 @@ problem_dropdown = gr.Dropdown(problem_numbers, label="Problem Number")
 def solve_problem(exam, year, problem):
     problem_statement = df[(df["exam name"] == exam) & (df["year"] == year) & (df["problem number"] == problem)]["problem statement"].values[0]
     prompt = f"Solve the following problem: {problem_statement}"
-    response = client.text_generation(prompt, max_new_tokens=512, temperature=0.7, top_p=0.95)
+    response = client.text_generation(prompt, max_new_tokens=512, temperature=0.7, top_p=0.95, model = "HuggingFaceH4/zephyr-7b-beta")
     return response[0]['generated_text']
 
 def give_hints(exam, year, problem):
     problem_statement = df[(df["exam name"] == exam) & (df["year"] == year) & (df["problem number"] == problem)]["problem statement"].values[0]
     prompt = f"Give hints for the following problem: {problem_statement}"
-    response = client.text_generation(prompt, max_new_tokens=512, temperature=0.7, top_p=0.95)
+    response = client.text_generation(prompt, max_new_tokens=512, temperature=0.7, top_p=0.95, model = "HuggingFaceH4/zephyr-7b-beta")
     return response[0]['generated_text']
 
 def create_similar_problem(exam, year, problem):
     problem_statement = df[(df["exam name"] == exam) & (df["year"] == year) & (df["problem number"] == problem)]["problem statement"].values[0]
     prompt = f"Create a similar problem to the following one: {problem_statement}"
-    response = client.text_generation(prompt, max_new_tokens=512, temperature=0.7, top_p=0.95)
+    response = client.text_generation(prompt, max_new_tokens=512, temperature=0.7, top_p=0.95, model = "HuggingFaceH4/zephyr-7b-beta")
     return response[0]['generated_text']
 
 # Define the chat response function