Pull OPUS-100 en-zh for SFT instead of a checked-in jsonl

train_sft --data opus-100 streams Helsinki-NLP/opus-100, writes both
directions, and skips frozen eval sentences. Runtime cache stays under
data/sft/ (gitignored).

train_sft.py

@@ -1,9 +1,9 @@
 """Instruction SFT for zh↔en translation. Prompt template matches eval_mt.
 
 用法:
-    uv run python train_sft.py --ckpt ckpts/k3_wiki.pt --data data/sft/train.jsonl
-    uv run python train_sft.py --ckpt ckpts/k3_0.5b_best.pt --data data/sft/opus.jsonl \\
-        --seq-len 512 --batch 4 --lr 5e-5 --epochs 2
+    uv run python train_sft.py --ckpt ckpts/k3_wiki.pt --data data/sft/toy.jsonl
+    uv run python train_sft.py --ckpt ckpts/k3_0.5b_best.pt --data opus-100 \\
+        --limit 100000 --seq-len 512 --batch 4 --lr 5e-5 --epochs 2
 """
 
 from __future__ import annotations
@@ -18,7 +18,7 @@ from kda.layers.latent_moe import moe_router_losses
 from kda.training.data import (
     IGNORE_INDEX,
     iter_sft_batches,
-    load_sft_rows,
+    resolve_sft_rows,
     load_tokenizer,
 )
 from kda.training.eval_mt import evaluate_pairs
@@ -72,7 +72,22 @@ def _read_lines(path: str) -> list[str]:
 def main() -> None:
     p = argparse.ArgumentParser(description=__doc__)
     p.add_argument("--ckpt", required=True)
-    p.add_argument("--data", required=True, help="jsonl {src,tgt,target_lang} or TSV")
+    p.add_argument(
+        "--data",
+        default="opus-100",
+        help="local jsonl/tsv, or 'opus-100' to stream Helsinki-NLP/opus-100 en-zh",
+    )
+    p.add_argument(
+        "--limit",
+        type=int,
+        default=100_000,
+        help="OPUS source pairs to pull (each becomes zh2en + en2zh unless --one-dir)",
+    )
+    p.add_argument(
+        "--one-dir",
+        action="store_true",
+        help="only zh→en rows when pulling OPUS",
+    )
     p.add_argument("--out", default="ckpts/k3_sft.pt")
     p.add_argument("--tokenizer", default=None)
     p.add_argument("--batch", type=int, default=4)
@@ -103,9 +118,13 @@ def main() -> None:
     if not tok_src:
         raise SystemExit("need --tokenizer or a tokenizer field in the checkpoint")
     tok = load_tokenizer(tok_src)
-    rows = load_sft_rows(args.data)
+    rows = resolve_sft_rows(
+        args.data,
+        limit=args.limit,
+        both_dirs=not args.one_dir,
+    )
     if not rows:
-        raise SystemExit(f"no SFT rows in {args.data}")
+        raise SystemExit(f"no SFT rows from {args.data}")
     print(f"SFT {len(rows)} rows from {args.data}; model {cfg.__class__.__name__}")
 
     steps_per_epoch = max((len(rows) + args.batch - 1) // args.batch, 1)