diff --git a/models/gpt2/config.py b/models/gpt2/config.py
index 94d7bd1..8ed2d96 100644
--- a/models/gpt2/config.py
+++ b/models/gpt2/config.py
@@ -18,4 +18,4 @@
 # T - decode step size
 def get_config():
     config = collections.namedtuple('Config', ['B', 'K', 'S', 'T'])
-    return config(4, 8, 64, 1)
\ No newline at end of file
+    return config(1, 8, 64, 1)
diff --git a/models/gpt2/example_gen_test.py b/models/gpt2/example_gen_test.py
new file mode 100644
index 0000000..455dc73
--- /dev/null
+++ b/models/gpt2/example_gen_test.py
@@ -0,0 +1,46 @@
+import jax
+import jax.numpy as jnp
+
+import os
+import sys
+
+from transformers import GPT2Tokenizer
+
+tknzr = GPT2Tokenizer.from_pretrained("gpt2")
+
+import model
+import config
+
+assert_dir = os.path.join(sys.path[0], "assets")
+
+ids = tknzr.encode("Hello, my dog is cute")
+
+params = model.load_gpt2_model("gpt2", assert_dir)
+
+cfg = config.get_config()
+B = cfg.B  # Batch size
+K = cfg.K  # Input sequence length
+S = cfg.S
+T = cfg.T  # Batched decode
+L, _, _, Q, H, _ = model.model_sizes["gpt2"]
+
+nids = len(ids)
+t = jnp.asarray([nids], dtype=jnp.int32)
+prompt = jnp.asarray([ids + [0] * (K - nids)], dtype=jnp.int32)
+# t = [6]
+# prompt = [[15496    11   616  3290   318 13779     0     0]]
+
+
+kv = model.init_kv(1, S, L, Q, H, dtype=jnp.float32)
+kv = [jnp.tile(k, (1, prompt.shape[0], 1, 1, 1)) for k in kv]
+kv, x = model.encode(params, kv, prompt, 0, t)
+ids.append(x.item())
+
+for _ in range(12):
+    kv, x = model.decode(params, kv, x, t)
+    t = t + 1
+    ids.append(x.item())
+# ids = [15496, 11, 616, 3290, 318, 13779, 13, 314, 1101, 407, 1654, 611, 673, 338, 257, 26188, 393, 407, 13]
+assert (
+    tknzr.decode(ids) == "Hello, my dog is cute. I'm not sure if she's a puppy or not."
+)