moved files and restructured

.gitignore

@@ -42,3 +42,4 @@ logs/
 
 # Ignore node_modules
 node_modules/
+Article-Bias-Prediction/

datasettesting.py

@@ -1,6 +0,0 @@
-from datasets import load_dataset
-
-dataset = load_dataset("newsmediabias/instruction-safe-llm")
-
-
-print(dataset)

politicalbiasbertmodel.py

@@ -1,34 +0,0 @@
-from transformers import AutoTokenizer, AutoModelForSequenceClassification
-import torch
-
-# Load model and tokenizer
-model_name = "bucketresearch/politicalBiasBERT"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForSequenceClassification.from_pretrained(model_name)
-
-# Send model to GPU if available
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-model.to(device)
-
-# Label mapping
-label_mapping = {0: "Left", 1: "Center", 2: "Right"}
-
-# Inference loop
-def predict_bias(text):
-    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True, max_length=512).to(device)
-    with torch.no_grad():
-        outputs = model(**inputs)
-        logits = outputs.logits
-        probs = torch.softmax(logits, dim=-1)[0]
-        pred = torch.argmax(probs).item()
-        return label_mapping[pred], probs.tolist()
-
-if __name__ == "__main__":
-    print("Political Bias Classifier (bucketresearch/politicalBiasBERT)")
-    while True:
-        text = input("\nEnter text to classify (or type 'exit' to quit): ")
-        if text.lower() == "exit":
-            break
-        label, confidence = predict_bias(text)
-        print(f"Predicted Bias: {label}")
-        print(f"Confidence Scores: {confidence}")