diff --git a/.gitignore b/.gitignore
index 6518953..0944657 100644
--- a/.gitignore
+++ b/.gitignore
@@ -13,5 +13,7 @@
 # Large scaling-run corpora + tokenized id caches live on dash5 only, never in
 # git (the small data/tinystories-valid-3mb.txt is committed as a fixture).
 /data/tinystories-train.txt
+/data/fineweb-edu.txt
+/data/*.parquet
 *.u16.bin
 *.ckpt
diff --git a/scripts/fineweb_to_txt.py b/scripts/fineweb_to_txt.py
new file mode 100644
index 0000000..ef36fb6
--- /dev/null
+++ b/scripts/fineweb_to_txt.py
@@ -0,0 +1,59 @@
+#!/usr/bin/env python3
+"""FineWeb-edu parquet -> plain UTF-8 .txt for xtrain's Corpus loader (Scaling v6).
+
+v0-v5 trained on TinyStories; v6 broadens the data to FineWeb-edu
+(HuggingFaceFW/fineweb-edu, the `sample/10BT` subset) to isolate the
+data-source variable while keeping the v4/v5 architecture fixed.
+
+xtrain's `Corpus::load` (crates/xtrain-train/src/data.rs) reads a UTF-8 text
+file and tokenizes it with the gpt2 BPE; it treats `<|endoftext|>` as the
+document boundary (the gpt2 tokenizer emits id 50256 for it). This script
+extracts the `text` column from one or more FineWeb-edu parquet shards and
+writes each document followed by `<|endoftext|>`, producing exactly that
+format. Reads row-group by row-group so memory stays bounded regardless of
+shard size.
+
+Usage (on dash5, in data/):
+    python3 scripts/fineweb_to_txt.py OUT.txt SHARD1.parquet [SHARD2.parquet ...]
+
+The corpus / .txt / .u16.bin caches are multi-GB and live on dash5 only
+(gitignored); only this script is committed.
+"""
+
+import sys
+import pyarrow.parquet as pq
+
+EOS = "<|endoftext|>"
+
+
+def main() -> None:
+    if len(sys.argv) < 3:
+        sys.exit(f"usage: {sys.argv[0]} OUT.txt SHARD.parquet [SHARD.parquet ...]")
+    out_path = sys.argv[1]
+    shards = sys.argv[2:]
+
+    docs = 0
+    chars = 0
+    with open(out_path, "w", encoding="utf-8") as out:
+        for shard in shards:
+            pf = pq.ParquetFile(shard)
+            n_rg = pf.num_row_groups
+            print(f"{shard}: {pf.metadata.num_rows} rows, {n_rg} row groups", flush=True)
+            for rg in range(n_rg):
+                col = pf.read_row_group(rg, columns=["text"]).column("text")
+                for s in col:
+                    text = s.as_py()
+                    if text is None:
+                        continue
+                    out.write(text)
+                    out.write(EOS)
+                    docs += 1
+                    chars += len(text)
+            print(f"  done {shard}: cumulative {docs} docs", flush=True)
+
+    print(f"wrote {out_path}: {docs} docs, {chars} text chars "
+          f"(+ {docs} x '{EOS}' separators)", flush=True)
+
+
+if __name__ == "__main__":
+    main()