🚀 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.

build_full_bits.py

@@ -0,0 +1,23 @@
+import pathlib
+import torch
+from datasets import load_dataset
+
+TXT_MB = 100
+OUT = pathlib.Path('full_bits.pt')
+
+
+def build_bits(out: pathlib.Path = OUT, txt_mb: int = TXT_MB) -> None:
+    ds = load_dataset('wikitext', 'wikitext-2-raw-v1', split='train')
+    buf = bytearray()
+    for line in ds['text']:
+        buf.extend(line.encode() + b"\n")
+        if len(buf) >= txt_mb * 2 ** 20:
+            break
+    bits = []
+    for byte in buf:
+        bits.extend(int(b) for b in f'{byte:08b}')
+    tensor = torch.tensor(bits, dtype=torch.uint8)
+    torch.save(tensor, out)
+
+if __name__ == '__main__':
+    build_bits()