🚀 OS Launch: Clean documentation and refined licensing

This OS launch commit includes:

✅ **Cleaned Documentation**
- Removed inflated claims and marketing language
- Added honest research status and limitations
- Created professional model card and validation reports
- Streamlined licensing to AGPLv3 + commercial contact

✅ **Refined Codebase**
- Complete experimental bit-native transformer implementation
- 57 Python files with comprehensive research framework
- Safety telemetry and monitoring systems
- Distributed training and development tools

✅ **Professional Standards**
- Empirical validation of all claims
- Clear experimental vs production distinctions
- Rigorous research methodology requirements
- Community contribution framework

Ready for serious research evaluation and academic investigation.

create_dataset.py

@@ -0,0 +1,61 @@
+#!/usr/bin/env python3
+"""
+BitTransformerLM Dataset Creation Script
+
+Usage:
+    python create_dataset.py --token YOUR_HF_TOKEN --repo-id YOUR_REPO_NAME
+
+This script creates a comprehensive dataset for BitTransformerLM training
+and uploads it to HuggingFace Hub with proper metadata and organization.
+"""
+
+import argparse
+import sys
+from pathlib import Path
+
+# Add the bit_transformer module to path
+sys.path.insert(0, str(Path(__file__).parent))
+
+from bit_transformer.dataset_builder import create_bittransformerlm_dataset
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Create BitTransformerLM Dataset")
+    parser.add_argument("--token", required=True, help="HuggingFace access token")
+    parser.add_argument("--repo-id", default="BitTransformerLM", help="Dataset repository ID")
+    parser.add_argument("--private", action="store_true", default=True, help="Make dataset private")
+    parser.add_argument("--samples", type=int, default=25000, help="Total number of samples")
+    
+    args = parser.parse_args()
+    
+    print("🚀 Starting BitTransformerLM Dataset Creation")
+    print(f"Repository: {args.repo_id}")
+    print(f"Private: {args.private}")
+    print(f"Target samples: {args.samples}")
+    print("-" * 50)
+    
+    try:
+        dataset_url = create_bittransformerlm_dataset(
+            hf_token=args.token,
+            repo_id=args.repo_id
+        )
+        
+        print("\n" + "=" * 50)
+        print("🎉 SUCCESS! Dataset created and uploaded")
+        print(f"📍 URL: {dataset_url}")
+        print("=" * 50)
+        
+        print("\n📋 Next Steps:")
+        print("1. View your dataset on HuggingFace Hub")
+        print("2. Test loading with: `from datasets import load_dataset`")
+        print("3. Integrate with BitTransformerLM training pipeline")
+        print("4. Monitor dataset usage and performance metrics")
+        
+    except Exception as e:
+        print(f"\n❌ ERROR: {e}")
+        print("Please check your token and repository permissions.")
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()