Update organization

huggingface · Nov 7, 2022 · 5411c16 · 5411c16
1 parent 545b026
commit 5411c16
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Showing 2 changed files with 15 additions and 17 deletions.
diff --git a/src/transformers/models/clipseg/modeling_clipseg.py b/src/transformers/models/clipseg/modeling_clipseg.py
@@ -39,11 +39,10 @@
 logger = logging.get_logger(__name__)
 
 
-_CHECKPOINT_FOR_DOC = "nielsr/clipseg-rd64-refined"
+_CHECKPOINT_FOR_DOC = "CIDAS/clipseg-rd64-refined"
 
 CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST = [
-    # TODO update organziation
-    "nielsr/clipseg-rd64-refined",
+    "CIDAS/clipseg-rd64-refined",
     # See all CLIPSeg models at https://huggingface.co/models?filter=clipseg
 ]
 
@@ -807,8 +806,8 @@ def forward(
         ```python
         >>> from transformers import CLIPTokenizer, CLIPSegTextModel
 
-        >>> tokenizer = CLIPTokenizer.from_pretrained("nielsr/clipseg-rd64-refined")
-        >>> model = CLIPSegTextModel.from_pretrained("nielsr/clipseg-rd64-refined")
+        >>> tokenizer = CLIPTokenizer.from_pretrained("CIDAS/clipseg-rd64-refined")
+        >>> model = CLIPSegTextModel.from_pretrained("CIDAS/clipseg-rd64-refined")
 
         >>> inputs = tokenizer(["a photo of a cat", "a photo of a dog"], padding=True, return_tensors="pt")
 
@@ -918,8 +917,8 @@ def forward(
         >>> import requests
         >>> from transformers import CLIPSegProcessor, CLIPSegVisionModel
 
-        >>> processor = CLIPSegProcessor.from_pretrained("nielsr/clipseg-rd64-refined")
-        >>> model = CLIPSegVisionModel.from_pretrained("nielsr/clipseg-rd64-refined")
+        >>> processor = CLIPSegProcessor.from_pretrained("CIDAS/clipseg-rd64-refined")
+        >>> model = CLIPSegVisionModel.from_pretrained("CIDAS/clipseg-rd64-refined")
 
         >>> url = "http://images.cocodataset.org/val2017/000000039769.jpg"
         >>> image = Image.open(requests.get(url, stream=True).raw)
@@ -994,8 +993,8 @@ def get_text_features(
         ```python
         >>> from transformers import CLIPTokenizer, CLIPSegModel
 
-        >>> tokenizer = CLIPTokenizer.from_pretrained("nielsr/clipseg-rd64-refined")
-        >>> model = CLIPSegModel.from_pretrained("nielsr/clipseg-rd64-refined")
+        >>> tokenizer = CLIPTokenizer.from_pretrained("CIDAS/clipseg-rd64-refined")
+        >>> model = CLIPSegModel.from_pretrained("CIDAS/clipseg-rd64-refined")
 
         >>> inputs = tokenizer(["a photo of a cat", "a photo of a dog"], padding=True, return_tensors="pt")
         >>> text_features = model.get_text_features(**inputs)
@@ -1041,8 +1040,8 @@ def get_image_features(
         >>> import requests
         >>> from transformers import CLIPSegProcessor, CLIPSegModel
 
-        >>> processor = CLIPSegProcessor.from_pretrained("nielsr/clipseg-rd64-refined")
-        >>> model = CLIPSegModel.from_pretrained("nielsr/clipseg-rd64-refined")
+        >>> processor = CLIPSegProcessor.from_pretrained("CIDAS/clipseg-rd64-refined")
+        >>> model = CLIPSegModel.from_pretrained("CIDAS/clipseg-rd64-refined")
 
         >>> url = "http://images.cocodataset.org/val2017/000000039769.jpg"
         >>> image = Image.open(requests.get(url, stream=True).raw)
@@ -1093,8 +1092,8 @@ def forward(
         >>> import requests
         >>> from transformers import CLIPSegProcessor, CLIPSegModel
 
-        >>> processor = CLIPSegProcessor.from_pretrained("nielsr/clipseg-rd64-refined")
-        >>> model = CLIPSegModel.from_pretrained("nielsr/clipseg-rd64-refined")
+        >>> processor = CLIPSegProcessor.from_pretrained("CIDAS/clipseg-rd64-refined")
+        >>> model = CLIPSegModel.from_pretrained("CIDAS/clipseg-rd64-refined")
 
         >>> url = "http://images.cocodataset.org/val2017/000000039769.jpg"
         >>> image = Image.open(requests.get(url, stream=True).raw)
@@ -1403,8 +1402,8 @@ def forward(
         >>> from PIL import Image
         >>> import requests
 
-        >>> processor = CLIPSegProcessor.from_pretrained("nielsr/clipseg-rd64-refined")
-        >>> model = CLIPSegForImageSegmentation.from_pretrained("nielsr/clipseg-rd64-refined")
+        >>> processor = CLIPSegProcessor.from_pretrained("CIDAS/clipseg-rd64-refined")
+        >>> model = CLIPSegForImageSegmentation.from_pretrained("CIDAS/clipseg-rd64-refined")
 
         >>> url = "http://images.cocodataset.org/val2017/000000039769.jpg"
         >>> image = Image.open(requests.get(url, stream=True).raw)

diff --git a/tests/models/clipseg/test_modeling_clipseg.py b/tests/models/clipseg/test_modeling_clipseg.py
@@ -706,8 +706,7 @@ def prepare_img():
 class CLIPSegModelIntegrationTest(unittest.TestCase):
     @slow
     def test_inference_image_segmentation(self):
-        # TODO update to appropriate organization
-        model_name = "nielsr/clipseg-rd64-refined"
+        model_name = "CIDAS/clipseg-rd64-refined"
         processor = CLIPSegProcessor.from_pretrained(model_name)
         model = CLIPSegForImageSegmentation.from_pretrained(model_name).to(torch_device)