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hugging/td_fuse/heal.py

@@ -347,6 +347,37 @@ def apply_qlora_standard(
 
     print(f"\n[heal] Merging LoRA adapters...")
     merged_model = model.merge_and_unload()
+
+    # Free disk space before saving — remove duplicate model copies
+    import shutil, gc
+    print("[heal] Freeing disk space before save...")
+
+    # Search for large duplicate directories we can safely remove
+    # The healed model in memory IS the final product — we don't need old copies
+    cleanup_targets = [
+        "td_fuse_outputs/final",           # duplicate of after_deepseek
+        "td_fuse_outputs/healed",          # old healed dir if exists
+    ]
+    for target in cleanup_targets:
+        target_path = Path(target)
+        if target_path.exists() and target_path.is_dir():
+            shutil.rmtree(str(target_path))
+            print(f"[heal] Freed space: removed {target_path}")
+
+    # Remove any trainer checkpoint-* dirs (we have the merged model in memory)
+    for parent in [Path("."), Path("td_lang_outputs"), Path(cfg.output_dir)]:
+        if parent.exists():
+            for ckpt in parent.rglob("checkpoint-*"):
+                if ckpt.is_dir():
+                    shutil.rmtree(str(ckpt))
+                    print(f"[heal] Freed space: removed {ckpt}")
+
+    gc.collect()
+
+    # Report free space
+    stat = shutil.disk_usage("/")
+    print(f"[heal] Disk space: {stat.free / 1e9:.1f} GB free / {stat.total / 1e9:.1f} GB total")
+
     merged_model.save_pretrained(str(healed_dir))
     tokenizer.save_pretrained(str(healed_dir))