diff --git a/training/README.md b/training/README.md
index 8ccde88..a3f33eb 100644
--- a/training/README.md
+++ b/training/README.md
@@ -83,15 +83,17 @@ Downloads pretokenized TinyStories (Llama 2 BPE, 32K vocab) from HuggingFace. Pr
 ### 2. Build & Train
 
 ```bash
-# Static baseline (classifier + softmax on CPU)
-make train_large
-./train_large stories110M.bin 256 100 1e-4
-./train_large --model stories110M.bin --steps 100 --lr 1e-4
-
-# PR#19: ANE-offloaded classifier + softmax + rmsnorm_bwd
-make train_large_ane
-./train_large_ane stories110M.bin 256 100 1e-4
-./train_large_ane --no-ane-extras --steps 100    # disable ANE extras
+# Static baseline (classifier + softmax on CPU)
+make train_large
+./train_large stories110M.bin 256 100 1e-4
+./train_large --model stories110M.bin --steps 100 --lr 1e-4
+./train_large --data ./tinystories_data00.bin --steps 100 --lr 1e-4
+
+# PR#19: ANE-offloaded classifier + softmax + rmsnorm_bwd
+make train_large_ane
+./train_large_ane stories110M.bin 256 100 1e-4
+./train_large_ane --no-ane-extras --steps 100    # disable ANE extras
+./train_large_ane --data ./tinystories_data00.bin --steps 100 --lr 1e-4
 
 # Dynamic pipeline (no recompilation)
 cd training_dynamic && make train
@@ -100,13 +102,14 @@ cd training_dynamic && make train
 ./train --steps 200 --lr 1e-4  # custom steps/lr
 ```
 
-**CLI flags (all pipelines):**
+**CLI flags (`train_large` / `train_large_ane`):**
 - `--steps N` (default 10000)
-- `--lr F` (default 3e-4)
-- `--model PATH` — pretrained weights file
-- `--ckpt PATH` — checkpoint file (preserved across exec() restarts)
-- `--resume` — resume from checkpoint
-- `--no-ane-extras` — (train_large_ane only) disable ANE classifier/softmax/rmsnorm_bwd
+- `--lr F` (default 3e-4)
+- `--model PATH` — pretrained weights file
+- `--data PATH` — tokenized TinyStories `.bin` file (default: `tinystories_data00.bin`)
+- `--ckpt PATH` — checkpoint file (preserved across exec() restarts)
+- `--resume` — resume from checkpoint
+- `--no-ane-extras` — (train_large_ane only) disable ANE classifier/softmax/rmsnorm_bwd
 
 ### 3. Monitor with Dashboard
 
diff --git a/training/train_large.m b/training/train_large.m
index 8b83bfc..96f8f7a 100644
--- a/training/train_large.m
+++ b/training/train_large.m
@@ -5,9 +5,9 @@
 #include "stories_mil.h"
 #include "stories_cpu_ops.h"
 
-#define CKPT_PATH_DEFAULT "ane_stories110M_ckpt.bin"
-#define MODEL_PATH_DEFAULT "stories110M.bin"
-#define DATA_PATH "tinystories_data00.bin"
+#define CKPT_PATH_DEFAULT "ane_stories110M_ckpt.bin"
+#define MODEL_PATH_DEFAULT "stories110M.bin"
+#define DATA_PATH_DEFAULT "tinystories_data00.bin"
 
 // ===== Weight loading from llama2.c format =====
 static bool load_pretrained(LayerWeights *lw, float *rms_final, float *embed, const char *path) {
@@ -192,22 +192,24 @@ int main(int argc, char *argv[]) {
         float adam_b1=0.9f, adam_b2=0.999f, adam_eps=1e-8f;
         int adam_t = 0, start_step = 0;
 
-        // Parse args
-        const char *ckpt_path = CKPT_PATH_DEFAULT;
-        const char *model_path = MODEL_PATH_DEFAULT;
-        bool do_resume = false;
-        int pos = 0;
-        for (int i=1; i<argc; i++) {
-            if (strcmp(argv[i], "--resume") == 0) do_resume = true;
-            else if (strcmp(argv[i], "--steps") == 0 && i+1<argc) total_steps = atoi(argv[++i]);
-            else if (strcmp(argv[i], "--lr") == 0 && i+1<argc) lr = atof(argv[++i]);
-            else if (strcmp(argv[i], "--ckpt") == 0 && i+1<argc) ckpt_path = argv[++i];
-            else if (strcmp(argv[i], "--model") == 0 && i+1<argc) model_path = argv[++i];
-            else if (argv[i][0] != '-') {
-                if (pos == 0) model_path = argv[i];
-                else if (pos == 1) { /* seq - compile-time constant */ }
-                else if (pos == 2) total_steps = atoi(argv[i]);
-                else if (pos == 3) lr = atof(argv[i]);
+        // Parse args
+        const char *ckpt_path = CKPT_PATH_DEFAULT;
+        const char *model_path = MODEL_PATH_DEFAULT;
+        const char *data_path = DATA_PATH_DEFAULT;
+        bool do_resume = false;
+        int pos = 0;
+        for (int i=1; i<argc; i++) {
+            if (strcmp(argv[i], "--resume") == 0) do_resume = true;
+            else if (strcmp(argv[i], "--steps") == 0 && i+1<argc) total_steps = atoi(argv[++i]);
+            else if (strcmp(argv[i], "--lr") == 0 && i+1<argc) lr = atof(argv[++i]);
+            else if (strcmp(argv[i], "--ckpt") == 0 && i+1<argc) ckpt_path = argv[++i];
+            else if (strcmp(argv[i], "--model") == 0 && i+1<argc) model_path = argv[++i];
+            else if (strcmp(argv[i], "--data") == 0 && i+1<argc) data_path = argv[++i];
+            else if (argv[i][0] != '-') {
+                if (pos == 0) model_path = argv[i];
+                else if (pos == 1) { /* seq - compile-time constant */ }
+                else if (pos == 2) total_steps = atoi(argv[i]);
+                else if (pos == 3) lr = atof(argv[i]);
                 pos++;
             }
         }
@@ -283,8 +285,12 @@ int main(int argc, char *argv[]) {
         }
 
         // mmap token data
-        int data_fd = open(DATA_PATH, O_RDONLY);
-        if (data_fd < 0) { printf("Cannot open %s\n", DATA_PATH); return 1; }
+        int data_fd = open(data_path, O_RDONLY);
+        if (data_fd < 0) {
+            printf("Cannot open token data: %s\n", data_path);
+            printf("Hint: run `bash download_data.sh` in training/ or pass --data /path/to/tinystories_data00.bin\n");
+            return 1;
+        }
         struct stat st; fstat(data_fd, &st);
         size_t data_len = st.st_size;
         uint16_t *token_data = (uint16_t*)mmap(NULL, data_len, PROT_READ, MAP_PRIVATE, data_fd, 0);
@@ -346,9 +352,9 @@ int main(int argc, char *argv[]) {
                     lw, la, rms_final, &arms_final, embed, &aembed);
                 printf("[exec() restart step %d, %d compiles, loss=%.4f]\n", step, g_compile_count, last_loss);
                 fflush(stdout);
-                execl(argv[0], argv[0], "--resume", "--ckpt", ckpt_path, NULL);
-                perror("execl"); return 1;
-            }
+                execl(argv[0], argv[0], "--resume", "--ckpt", ckpt_path, "--data", data_path, NULL);
+                perror("execl"); return 1;
+            }
 
             // Compile all layers' weight-bearing kernels
             uint64_t tc = mach_absolute_time();
diff --git a/training/train_large_ane.m b/training/train_large_ane.m
index ba9dfe7..25e9160 100644
--- a/training/train_large_ane.m
+++ b/training/train_large_ane.m
@@ -9,7 +9,7 @@
 //               NLL loss + gradient (needs target indexing)
 //
 // Build: make train_large_ane
-// Run:   ./train_large_ane [--resume] [--steps N] [--lr F]
+// Run:   ./train_large_ane [--resume] [--steps N] [--lr F] [--data PATH]
 #include "stories_io.h"
 #include "stories_mil.h"
 #include "stories_cpu_ops.h"
@@ -18,7 +18,7 @@
 
 #define CKPT_PATH_DEFAULT "ane_stories110M_ckpt.bin"
 #define MODEL_PATH_DEFAULT "stories110M.bin"
-#define DATA_PATH "tinystories_data00.bin"
+#define DATA_PATH_DEFAULT "tinystories_data00.bin"
 
 // ===== Weight loading from llama2.c format =====
 static bool load_pretrained(LayerWeights *lw, float *rms_final, float *embed, const char *path) {
@@ -204,6 +204,7 @@ int main(int argc, char *argv[]) {
         int adam_t = 0, start_step = 0;
         const char *ckpt_path = CKPT_PATH_DEFAULT;
         const char *model_path = MODEL_PATH_DEFAULT;
+        const char *data_path = DATA_PATH_DEFAULT;
         bool do_resume = false;
         bool ane_extras = true;  // classifier, softmax, rmsnorm_bwd on ANE
         int pos = 0;
@@ -214,6 +215,7 @@ int main(int argc, char *argv[]) {
             else if (strcmp(argv[i], "--lr") == 0 && i+1<argc) lr = atof(argv[++i]);
             else if (strcmp(argv[i], "--ckpt") == 0 && i+1<argc) ckpt_path = argv[++i];
             else if (strcmp(argv[i], "--model") == 0 && i+1<argc) model_path = argv[++i];
+            else if (strcmp(argv[i], "--data") == 0 && i+1<argc) data_path = argv[++i];
             else if (argv[i][0] != '-') {
                 if (pos == 0) model_path = argv[i];
                 else if (pos == 1) { /* seq - compile-time constant */ }
@@ -271,8 +273,12 @@ int main(int argc, char *argv[]) {
         }
 
         // mmap token data
-        int data_fd = open(DATA_PATH, O_RDONLY);
-        if (data_fd < 0) { printf("Cannot open %s\n", DATA_PATH); return 1; }
+        int data_fd = open(data_path, O_RDONLY);
+        if (data_fd < 0) {
+            printf("Cannot open token data: %s\n", data_path);
+            printf("Hint: run `bash download_data.sh` in training/ or pass --data /path/to/tinystories_data00.bin\n");
+            return 1;
+        }
         struct stat st; fstat(data_fd, &st);
         size_t data_len = st.st_size;
         uint16_t *token_data = (uint16_t*)mmap(NULL, data_len, PROT_READ, MAP_PRIVATE, data_fd, 0);
@@ -354,9 +360,9 @@ int main(int argc, char *argv[]) {
                 printf("[exec() restart step %d, %d compiles, loss=%.4f]\n", step, g_compile_count, last_loss);
                 fflush(stdout);
                 if (ane_extras)
-                    execl(argv[0], argv[0], "--resume", "--ckpt", ckpt_path, NULL);
+                    execl(argv[0], argv[0], "--resume", "--ckpt", ckpt_path, "--data", data_path, NULL);
                 else
-                    execl(argv[0], argv[0], "--resume", "--ckpt", ckpt_path, "--no-ane-extras", NULL);
+                    execl(argv[0], argv[0], "--resume", "--ckpt", ckpt_path, "--data", data_path, "--no-ane-extras", NULL);
                 perror("execl"); return 1;
             }