diff --git a/toolkit/kohya_model_util.py b/toolkit/kohya_model_util.py
index 5e976f0b..798fc2dc 100644
--- a/toolkit/kohya_model_util.py
+++ b/toolkit/kohya_model_util.py
@@ -892,6 +892,9 @@ def convert_ldm_clip_checkpoint_v1(checkpoint):
     for key in keys:
         if key.startswith("cond_stage_model.transformer"):
             text_model_dict[key[len("cond_stage_model.transformer."):]] = checkpoint[key]
+    # support checkpoint without position_ids (invalid checkpoint)
+    if "text_model.embeddings.position_ids" not in text_model_dict:
+        text_model_dict["text_model.embeddings.position_ids"] = torch.arange(77).unsqueeze(0)  # 77 is the max length of the text
     return text_model_dict
 
 
@@ -1257,6 +1260,10 @@ def load_models_from_stable_diffusion_checkpoint(v2, ckpt_path, device="cpu", dt
         text_model = CLIPTextModel.from_pretrained("openai/clip-vit-large-patch14").to(device)
         logging.set_verbosity_warning()
 
+        # latest transformers doesnt have position ids. Do we remove it?
+        if "text_model.embeddings.position_ids" not in text_model.state_dict():
+            del converted_text_encoder_checkpoint["text_model.embeddings.position_ids"]
+
         info = text_model.load_state_dict(converted_text_encoder_checkpoint)
     print("loading text encoder:", info)