up

.idea/.gitignore

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+# Default ignored files
+/shelf/
+/workspace.xml
+# Editor-based HTTP Client requests
+/httpRequests/
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml

.idea/inspectionProfiles/Project_Default.xml

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+<component name="InspectionProjectProfileManager">
+  <profile version="1.0">
+    <option name="myName" value="Project Default" />
+    <inspection_tool class="PyPackageRequirementsInspection" enabled="true" level="WARNING" enabled_by_default="true">
+      <option name="ignoredPackages">
+        <value>
+          <list size="10">
+            <item index="0" class="java.lang.String" itemvalue="tensorstore" />
+            <item index="1" class="java.lang.String" itemvalue="pytorch-lightning" />
+            <item index="2" class="java.lang.String" itemvalue="lxml" />
+            <item index="3" class="java.lang.String" itemvalue="torchvision" />
+            <item index="4" class="java.lang.String" itemvalue="pytorch-pretrained-biggan" />
+            <item index="5" class="java.lang.String" itemvalue="kornia" />
+            <item index="6" class="java.lang.String" itemvalue="accelerate" />
+            <item index="7" class="java.lang.String" itemvalue="fire" />
+            <item index="8" class="java.lang.String" itemvalue="einops" />
+            <item index="9" class="java.lang.String" itemvalue="retry" />
+          </list>
+        </value>
+      </option>
+    </inspection_tool>
+  </profile>
+</component>

.idea/inspectionProfiles/profiles_settings.xml

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+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 2.7" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/whisper-tiny.iml" filepath="$PROJECT_DIR$/.idea/whisper-tiny.iml" />
+    </modules>
+  </component>
+</project>

.idea/vcs.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="" vcs="Git" />
+  </component>
+</project>

.idea/whisper-tiny.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

README.md

@@ -351,7 +351,8 @@ This code snippet shows how to evaluate Whisper Tiny on [LibriSpeech test-clean]
 The Whisper model is intrinsically designed to work on audio samples of up to 30s in duration. However, by using a chunking 
 algorithm, it can be used to transcribe audio samples of up to arbitrary length. This is possible through Transformers 
 [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline) 
-method, which can also be extended to predict utterance level timestamps:
+method. Chunking is enabled by setting `chunk_length_s=30` when instantiating the pipeline. It can also be extended to 
+predict utterance level timestamps by passing `return_timestamps=True`:
 
 ```python
 >>> import torch