diff --git a/src/diffusers/pipelines/stable_diffusion/convert_from_ckpt.py b/src/diffusers/pipelines/stable_diffusion/convert_from_ckpt.py
index 42e8ae7cafd2..ff9e03d29347 100644
--- a/src/diffusers/pipelines/stable_diffusion/convert_from_ckpt.py
+++ b/src/diffusers/pipelines/stable_diffusion/convert_from_ckpt.py
@@ -727,8 +727,8 @@ def _copy_layers(hf_layers, pt_layers):
     return hf_model
 
 
-def convert_ldm_clip_checkpoint(checkpoint):
-    text_model = CLIPTextModel.from_pretrained("openai/clip-vit-large-patch14")
+def convert_ldm_clip_checkpoint(checkpoint, local_files_only=False):
+    text_model = CLIPTextModel.from_pretrained("openai/clip-vit-large-patch14", local_files_only=local_files_only)
 
     keys = list(checkpoint.keys())
 
@@ -992,6 +992,7 @@ def download_from_original_stable_diffusion_ckpt(
     controlnet: Optional[bool] = None,
     load_safety_checker: bool = True,
     pipeline_class: DiffusionPipeline = None,
+    local_files_only=False
 ) -> DiffusionPipeline:
     """
     Load a Stable Diffusion pipeline object from a CompVis-style `.ckpt`/`.safetensors` file and (ideally) a `.yaml`
@@ -1037,6 +1038,8 @@ def download_from_original_stable_diffusion_ckpt(
             Whether to load the safety checker or not. Defaults to `True`.
         pipeline_class (`str`, *optional*, defaults to `None`):
             The pipeline class to use. Pass `None` to determine automatically.
+        local_files_only (`bool`, *optional*, defaults to `False`):
+            Whether or not to only look at local files (i.e., do not try to download the model).
         return: A StableDiffusionPipeline object representing the passed-in `.ckpt`/`.safetensors` file.
     """
 
@@ -1292,7 +1295,7 @@ def download_from_original_stable_diffusion_ckpt(
             feature_extractor=feature_extractor,
         )
     elif model_type == "FrozenCLIPEmbedder":
-        text_model = convert_ldm_clip_checkpoint(checkpoint)
+        text_model = convert_ldm_clip_checkpoint(checkpoint, local_files_only=local_files_only)
         tokenizer = CLIPTokenizer.from_pretrained("openai/clip-vit-large-patch14")
 
         if load_safety_checker: