Upload unsloth_train.py with huggingface_hub

unsloth_train.py

@@ -78,13 +78,25 @@ def main():
     model.print_trainable_parameters()
 
     print("[2/4] loading dataset", flush=True)
-    if os.path.isdir(args.data):
-        shards = sorted(glob.glob(os.path.join(args.data, "*.jsonl.gz")))
-        if not shards:
-            sys.exit("no *.jsonl.gz in %s" % args.data)
-        print("[2/4] %d shards" % len(shards), flush=True)
-    else:
-        shards = [args.data]
+    # robust: if the given path is missing, search common locations
+    candidates = [args.data]
+    if not os.path.exists(args.data):
+        candidates += ["/root/baap-ds/data", "/root/baap-data",
+                       "/root/baap-ds", "/root/data", "/root"]
+    shards = []
+    for c in candidates:
+        if os.path.isdir(c):
+            found = sorted(glob.glob(os.path.join(c, "**", "*.jsonl.gz"),
+                                    recursive=True))
+            if found:
+                shards = found
+                print("[2/4] found %d shards in %s" % (len(shards), c), flush=True)
+                break
+        elif os.path.isfile(c):
+            shards = [c]
+            break
+    if not shards:
+        sys.exit("no *.jsonl.gz found (tried: %s)" % ", ".join(candidates))
     ds = load_dataset("json", data_files=shards, split="train")
     if args.limit:
         ds = ds.select(range(args.limit))