v10.1

- Bug fixes

Author: MitchellShibilski-Unkel

AI/__pycache__/aiScoring.cpython-312.pyc

@@ -6,8 +6,6 @@ def score(_in, device, test: int = 1, inputSize: int = 16, hx: int = 32, outputS
     startTimer = time.perf_counter()
     startTimer2 = time.process_time()
 
-    change = 0 # Placeholder for HuggingFace
-    
     if test == 1:
         SimpleNeuralNet(inputSize, hx, outputSize).to(device)(_in)
     elif test == 2:
@@ -24,5 +22,5 @@ def score(_in, device, test: int = 1, inputSize: int = 16, hx: int = 32, outputS
     endTimer2 = time.process_time()
 
     totalTime = (endTimer - startTimer) + (endTimer2 - startTimer2)
-    points = (1000 // totalTime * 0.1) + change
+    points = (1000 // totalTime * 0.1)
     return f"AI Score: {points} | Time Taken: {totalTime}s"

AI/__pycache__/aiTests.cpython-312.pyc

@@ -1,4 +1,5 @@
 from torch import nn
+from transformers import pipeline
 
 
 class SimpleNeuralNet(nn.Module):
@@ -68,6 +69,5 @@ def __init__(self, modelName: str = "google/gemma-3-270m", device: str = "cpu",
         self.type = type
 
     def model(self, data):
-        from transformers import pipeline
         pipe = pipeline(self.type, self.modelName, device=self.device)(data)
         return pipe

AI/aiScoring.py

@@ -44,10 +44,7 @@ def terminal(l = [], a = 0, b = 0, l2 = []):
         elif whichAI == "LargeNeuralNet" or whichAI == "3":
             return score(data, device, test=3, inputSize=inputSize, hx=hx, outputSize=outputSize, numLayers=numLayers)
         elif whichAI == "HuggingFace" or whichAI == "4":
-            usePrompt = input("Use a Custom Prompt? [y/n]: ")
-            if usePrompt == "y":
-                prompt = input("Enter Your Prompt [string/list]: ")
-                data = prompt
+            data = input("Prompt: ")
             modelName = input("HuggingFace Model Name (Default google/gemma-3-270m): ") or "google/gemma-3-270m"
             modelType = input("HuggingFace Model Type (Default text-generation): ") or "text-generation"
             return score(data, device, test=4, inputSize=inputSize, hx=0, outputSize=1, model=modelName, type=modelType)