fix transformers naming

Co-authored-by: yiyixuxu <yixu310@gmail,com>

docs/source/en/api/pipelines/stable_diffusion/panorama.mdx

@@ -25,12 +25,13 @@ Resources:
 * [Project Page](https://multidiffusion.github.io/).
 * [Paper](https://arxiv.org/abs/2302.08113).
 * [Original Code](https://github.com/omerbt/MultiDiffusion).
+* [Demo](https://huggingface.co/spaces/weizmannscience/MultiDiffusion).
 
 ## Available Pipelines:
 
-| Pipeline | Tasks
+| Pipeline | Tasks | Demo
-|---|---|
+|---|---|:---:|
-| [StableDiffusionPanoramaPipeline](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_panorama.py) | *Text-Guided Panorama View Generation* |
+| [StableDiffusionPanoramaPipeline](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_panorama.py) | *Text-Guided Panorama View Generation* | [🤗 Space](https://huggingface.co/spaces/weizmannscience/MultiDiffusion)) |
 
 <!-- TODO: add Colab -->
 

docs/source/en/api/pipelines/stable_diffusion/pix2pix_zero.mdx

@@ -14,7 +14,7 @@ specific language governing permissions and limitations under the License.
 
 ## Overview
 
-[Zero-shot Image-to-Image Translation](https://arxiv.org/abs/2302.03027) by Gaurav Parmar, Krishna Kumar Singh, Richard Zhang, Yijun Li, Jingwan Lu, and Jun-Yan Zhu.
+[Zero-shot Image-to-Image Translation](https://arxiv.org/abs/2302.03027).
 
 The abstract of the paper is the following:
 

setup.py

@@ -219,7 +219,7 @@ install_requires = [
 
 setup(
     name="diffusers",
-    version="0.13.0",  # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
+    version="0.13.1",  # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
     description="Diffusers",
     long_description=open("README.md", "r", encoding="utf-8").read(),
     long_description_content_type="text/markdown",

src/diffusers/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "0.13.0"
+__version__ = "0.13.1"
 
 from .configuration_utils import ConfigMixin
 from .utils import (

src/diffusers/pipelines/pipeline_utils.py

@@ -537,7 +537,7 @@ class DiffusionPipeline(ConfigMixin):
 
                 if revision in DEPRECATED_REVISION_ARGS and version.parse(
                     version.parse(__version__).base_version
-                ) >= version.parse("0.10.0"):
+                ) >= version.parse("0.15.0"):
                     info = model_info(
                         pretrained_model_name_or_path,
                         use_auth_token=use_auth_token,
@@ -825,7 +825,12 @@ class DiffusionPipeline(ConfigMixin):
                     loading_kwargs["sess_options"] = sess_options
 
                 is_diffusers_model = issubclass(class_obj, diffusers.ModelMixin)
-                transformers_version = version.parse(version.parse(transformers.__version__).base_version)
+
+                if is_transformers_available():
+                    transformers_version = version.parse(version.parse(transformers.__version__).base_version)
+                else:
+                    transformers_version = "N/A"
+
                 is_transformers_model = (
                     is_transformers_available()
                     and issubclass(class_obj, PreTrainedModel)

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_attend_and_excite.py

@@ -47,6 +47,7 @@ EXAMPLE_DOC_STRING = """
 
         >>> # use get_indices function to find out indices of the tokens you want to alter
         >>> pipe.get_indices(prompt)
+        {0: '<|startoftext|>', 1: 'a</w>', 2: 'cat</w>', 3: 'and</w>', 4: 'a</w>', 5: 'frog</w>', 6: '<|endoftext|>'}
 
         >>> token_indices = [2, 5]
         >>> seed = 6141
@@ -662,7 +663,7 @@ class StableDiffusionAttendAndExcitePipeline(DiffusionPipeline):
     def get_indices(self, prompt: str) -> Dict[str, int]:
         """Utility function to list the indices of the tokens you wish to alte"""
         ids = self.tokenizer(prompt).input_ids
-        indices = {tok: i for tok, i in zip(self.tokenizer.convert_ids_to_tokens(ids), range(len(ids)))}
+        indices = {i: tok for tok, i in zip(self.tokenizer.convert_ids_to_tokens(ids), range(len(ids)))}
         return indices
 
     @torch.no_grad()