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export_safetensors.py

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+"""Optional: export the weights as model.safetensors (run on your PC, then upload alongside sft.pt).
+
+    pip install safetensors
+    python export_safetensors.py
+"""
+import torch
+from safetensors.torch import save_file
+
+ck = torch.load("sft.pt", map_location="cpu", weights_only=False)
+sd = {k: v.contiguous() for k, v in ck["model"].items()}
+# weight tying: drop duplicates that share storage with the token embedding
+seen, out = {}, {}
+for k, v in sd.items():
+    ptr = v.data_ptr()
+    if ptr in seen:
+        continue
+    seen[ptr] = k
+    out[k] = v
+save_file(out, "model.safetensors", metadata={"format": "pt", "model": "sid-gpt-92m"})
+print(f"Wrote model.safetensors with {len(out)} tensors")