diff --git a/atomgpt/__init__.py b/atomgpt/__init__.py
index f10342f..2d76708 100644
--- a/atomgpt/__init__.py
+++ b/atomgpt/__init__.py
@@ -1,3 +1,3 @@
 """Version number."""
 
-__version__ = "2024.9.18"
+__version__ = "2024.9.30"
diff --git a/atomgpt/forward_models/forward_models.py b/atomgpt/forward_models/forward_models.py
index 3a030d4..3db48c1 100644
--- a/atomgpt/forward_models/forward_models.py
+++ b/atomgpt/forward_models/forward_models.py
@@ -29,7 +29,6 @@
 import pprint
 import sys
 import argparse
-from alignn.pretrained import get_figshare_model
 
 parser = argparse.ArgumentParser(
     description="Atomistic Generative Pre-trained Transformer."
@@ -287,10 +286,10 @@ def run_atomgpt(config_file="config.json"):
     pprint.pprint(config)
     id_prop_path = config.id_prop_path
     convert = config.convert
-    if convert:
-        model = get_figshare_model(
-            model_name="jv_formation_energy_peratom_alignn"
-        )
+    # if convert:
+    #    model = get_figshare_model(
+    #        model_name="jv_formation_energy_peratom_alignn"
+    #    )
     if ".zip" in id_prop_path:
         zp = zipfile.ZipFile(id_prop_path)
         dat = json.loads(zp.read(id_prop_path.split(".zip")[0]))
@@ -310,7 +309,8 @@ def run_atomgpt(config_file="config.json"):
             )
             if convert:
                 atoms = Atoms.from_poscar(pth)
-                lines = atoms.describe(model=model)[config.desc_type]
+                lines = atoms.describe()[config.desc_type]
+                # lines = atoms.describe(model=model)[config.desc_type]
             else:
 
                 with open(pth, "r") as f:
@@ -529,7 +529,9 @@ def run_atomgpt(config_file="config.json"):
             train_loss = 0
             # train_result = []
             input_ids = batch[0]["input_ids"].squeeze()  # .squeeze(0)
+            # print('input_ids',input_ids.shape)
             if "t5" in model_name:
+                input_ids = batch[0]["input_ids"].squeeze(1)  # .squeeze(0)
                 predictions = (
                     model(
                         input_ids.to(device),
@@ -571,7 +573,8 @@ def run_atomgpt(config_file="config.json"):
         f.write("id,target,predictions\n")
         with torch.no_grad():
             for batch in val_dataloader:
-                input_ids = batch[0]["input_ids"].squeeze()  # .squeeze(0)
+                # input_ids = batch[0]["input_ids"].squeeze()  # .squeeze(0)
+                input_ids = batch[0]["input_ids"].squeeze(1)  # .squeeze(0)
                 ids = batch[1]
                 if "t5" in model_name:
                     predictions = (
@@ -645,6 +648,9 @@ def run_atomgpt(config_file="config.json"):
                 for batch in test_dataloader:
                     input_ids = batch[0]["input_ids"].squeeze()  # .squeeze(0)
                     if "t5" in model_name:
+                        input_ids = batch[0]["input_ids"].squeeze(
+                            1
+                        )  # .squeeze(0)
                         predictions = (
                             model(
                                 input_ids.to(device),
diff --git a/setup.py b/setup.py
index 806e715..d3ac683 100644
--- a/setup.py
+++ b/setup.py
@@ -5,7 +5,7 @@
 
 setuptools.setup(
     name="atomgpt",
-    version="2024.9.18",
+    version="2024.9.30",
     author="Kamal Choudhary",
     author_email="kamal.choudhary@nist.gov",
     description="atomgpt",