Release v1.0.2: Implemented Style Prompting & Removed Grammar Correction

- Removed M2M100 Grammar Correction model completely to reduce bloat/complexity.
- Implemented 'Style Prompting' in Settings -> AI Engine to handle punctuation natively via Whisper.
- Added Style Presets: Standard (Default), Casual, and Custom.
- Optimized Build: Bootstrapper no longer requires transformers/sentencepiece.
- Fixed 'torch' NameError in Low VRAM mode.
- Fixed Bootstrapper missing dependency detection.
- Updated UI to reflect removed features.
- Included compiled v1.0.2 Executable in dist/.

test_m2m.py

@@ -0,0 +1,38 @@
+
+import sys
+from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
+
+def test_m2m():
+    model_name = "facebook/m2m100_418M"
+    print(f"Loading {model_name}...")
+    
+    tokenizer = M2M100Tokenizer.from_pretrained(model_name)
+    model = M2M100ForConditionalGeneration.from_pretrained(model_name)
+    
+    # Test cases: (Language Code, Input)
+    test_cases = [
+        ("en", "he go to school yesterday"),
+        ("pl", "on iść do szkoła wczoraj"), # Intentional broken grammar in Polish
+    ]
+    
+    print("\nStarting M2M Tests (Self-Translation):\n")
+    
+    for lang, input_text in test_cases:
+        tokenizer.src_lang = lang
+        encoded = tokenizer(input_text, return_tensors="pt")
+        
+        # Translate to SAME language
+        generated_tokens = model.generate(
+            **encoded, 
+            forced_bos_token_id=tokenizer.get_lang_id(lang)
+        )
+        
+        corrected = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0]
+        
+        print(f"[{lang}]")
+        print(f"Input:    {input_text}")
+        print(f"Output:   {corrected}")
+        print("-" * 20)
+
+if __name__ == "__main__":
+    test_m2m()