# WordVectorSerializer.readWord2VecModel throws an exception: "Unable to guess input file format"

**URL:** <https://community.konduit.ai/t/wordvectorserializer-readword2vecmodel-throws-an-exception-unable-to-guess-input-file-format/1003>\
**Category:** DL4J\
**Created:** [November 20, 2020, 1:58am UTC](https://community.konduit.ai/t/wordvectorserializer-readword2vecmodel-throws-an-exception-unable-to-guess-input-file-format/1003 "2020-11-20T01:58:50Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![hs2222](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/hs2222/32/362_2.png) [@hs2222](https://community.konduit.ai/u/hs2222)\
**Post date:** [November 20, 2020, 1:58am UTC](https://community.konduit.ai/t/wordvectorserializer-readword2vecmodel-throws-an-exception-unable-to-guess-input-file-format/1003/1 "2020-11-20T01:58:50Z")

</div>

> <https://github.com/eclipse/deeplearning4j/issues/9120>
>
> \#### Issue Description
> 
> I use WordVectorSerializer.readWord2VecModel to read m…odel which is saved by WordVectorSerializer.writeWord2VecModel, then I got an exception.
> WordVectorSerializer.readWord2VecModel is able to read a small word vector model, but failed to read a large one(about 1.2G).
> 
> \- expected behavior
> read model normally
> \- encountered behavior
> throw an exception
> 
> \#### Version Information
> 
> Please indicate relevant versions, including, if relevant:
> 
> \* Deeplearning4j version
> 1.0.0-beta7
> \* Platform information (OS, etc)
> Windows 10
> \* CUDA version, if used
> \* NVIDIA driver version, if in use
> 
> \#### Additional Information
> 
> Where applicable, please also provide:
> 
> \* Full log or exception stack trace (ideally in a Gist: gist.github.com)
> \`
> 23:40:13.762 \[main\] INFO org.nd4j.linalg.factory.Nd4jBackend - Loaded \[CpuBackend\] backend
> 23:40:14.968 \[main\] INFO org.nd4j.nativeblas.NativeOpsHolder - Number of threads used for linear algebra: 4
> 23:40:15.046 \[main\] INFO org.nd4j.nativeblas.Nd4jBlas - Number of threads used for OpenMP BLAS: 4
> 23:40:15.066 \[main\] INFO o.n.l.a.o.e.DefaultOpExecutioner - Backend used: \[CPU\]; OS: \[Windows 10\]
> 23:40:15.066 \[main\] INFO o.n.l.a.o.e.DefaultOpExecutioner - Cores: \[8\]; Memory: \[7.1GB\];
> 23:40:15.066 \[main\] INFO o.n.l.a.o.e.DefaultOpExecutioner - Blas vendor: \[OPENBLAS\]
> 23:40:36.342 \[main\] DEBUG o.d.m.e.loader.WordVectorSerializer - Trying simplified model restoration...
> 23:41:44.454 \[main\] DEBUG o.d.m.e.loader.WordVectorSerializer - Trying CSV model restoration...
> 23:41:44.463 \[main\] DEBUG o.d.m.e.loader.WordVectorSerializer - First line is a header
> 23:41:44.464 \[main\] DEBUG o.d.m.e.loader.WordVectorSerializer - Trying binary model restoration...
> 23:41:44.474 \[main\] ERROR o.d.m.e.loader.WordVectorSerializer - Cannot read binary model
> java.lang.NumberFormatException: For input string: "PK 7�cQ syn0.txt\\�۪��q����u��|ba�-����bH�\`;$�}�W���?E�"i}k�ﳙ�鮮�޳��j)?��������o��O{��~�����=ok�9K)������{e�����W��y�\]?�c���3�s/~��Z����Ywۥ�S�\<��\>�Y}���muV���zZ��ٺ.����Z����v��g�V\]����yΨ��^�,k�y�ޭ��z٭���8\\�ҫ�r�{�Z�͸���eꊗ�����ݣ�~��e��/��w���v���W�m�楧��7�6?���}���v\]�c���뛟U\]�=e�1���w�\[�c�����}�����ԯ��\[����t�\<s�Qܸ�yz;G�2g�×���zf�.\]������u�����f�Ʈ��z����K-�E}�\>x�z=g��9�\_����{\>��o�z���r���ZM��M������՗\\�M\]��w���7�\<֢\>�-�=�I�?nK�ͭ\]ЍO��������l�\>�ђ�zl��:t���lz!��}�ڧ�����ئ���R��=��sG�1����\]OGKu��oizc����9���ͷ�v�Һ�Zq�zˬ\`�ȫ���j�����%��fm��+S��U1��\]�q��k�{h)v=ס����Г��=���\[��G\[8�^����w���Z�Z"
> at java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)
> at java.lang.Integer.parseInt(Integer.java:580)
> at java.lang.Integer.parseInt(Integer.java:615)
> at org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.readBinaryModel(WordVectorSerializer.java:278)
> at org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.readAsBinaryNoLineBreaks(WordVectorSerializer.java:2444)
> at org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.readAsBinaryNoLineBreaks(WordVectorSerializer.java:2426)
> at org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.readWord2VecModel(WordVectorSerializer.java:2413)
> at org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.readWord2VecModel(WordVectorSerializer.java:2372)
> at org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.readWord2VecModel(WordVectorSerializer.java:2341)
> at com.tigerobo.javadl.inference.Dl4jWord2VecInference.\<clinit\>(Dl4jWord2VecInference.java:23)
> at com.tigerobo.javadl.Word2VecTest.nearestWords(Word2VecTest.java:30)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:50)
> at org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:12)
> at org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:47)
> at org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:17)
> at org.junit.runners.ParentRunner.runLeaf(ParentRunner.java:325)
> at org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:78)
> at org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:57)
> at org.junit.runners.ParentRunner$3.run(ParentRunner.java:290)
> at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:71)
> at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:288)
> at org.junit.runners.ParentRunner.access$000(ParentRunner.java:58)
> at org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:268)
> at org.junit.runners.ParentRunner.run(ParentRunner.java:363)
> at org.junit.runner.JUnitCore.run(JUnitCore.java:137)
> at com.intellij.junit4.JUnit4IdeaTestRunner.startRunnerWithArgs(JUnit4IdeaTestRunner.java:69)
> at com.intellij.rt.junit.IdeaTestRunner$Repeater.startRunnerWithArgs(IdeaTestRunner.java:33)
> at com.intellij.rt.junit.JUnitStarter.prepareStreamsAndStart(JUnitStarter.java:220)
> at com.intellij.rt.junit.JUnitStarter.main(JUnitStarter.java:53)
> 23:41:44.475 \[main\] ERROR o.d.m.e.loader.WordVectorSerializer - Unable to guess input file format
> java.lang.RuntimeException: Unable to guess input file format. Please use corresponding loader directly
> at org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.readAsBinaryNoLineBreaks(WordVectorSerializer.java:2447)
> at org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.readAsBinaryNoLineBreaks(WordVectorSerializer.java:2426)
> at org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.readWord2VecModel(WordVectorSerializer.java:2413)
> at org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.readWord2VecModel(WordVectorSerializer.java:2372)
> at org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.readWord2VecModel(WordVectorSerializer.java:2341)
> at com.tigerobo.javadl.inference.Dl4jWord2VecInference.\<clinit\>(Dl4jWord2VecInference.java:23)
> at com.tigerobo.javadl.Word2VecTest.nearestWords(Word2VecTest.java:30)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:50)
> at org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:12)
> at org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:47)
> at org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:17)
> at org.junit.runners.ParentRunner.runLeaf(ParentRunner.java:325)
> at org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:78)
> at org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:57)
> at org.junit.runners.ParentRunner$3.run(ParentRunner.java:290)
> at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:71)
> at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:288)
> at org.junit.runners.ParentRunner.access$000(ParentRunner.java:58)
> at org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:268)
> at org.junit.runners.ParentRunner.run(ParentRunner.java:363)
> at org.junit.runner.JUnitCore.run(JUnitCore.java:137)
> at com.intellij.junit4.JUnit4IdeaTestRunner.startRunnerWithArgs(JUnit4IdeaTestRunner.java:69)
> at com.intellij.rt.junit.IdeaTestRunner$Repeater.startRunnerWithArgs(IdeaTestRunner.java:33)
> at com.intellij.rt.junit.JUnitStarter.prepareStreamsAndStart(JUnitStarter.java:220)
> at com.intellij.rt.junit.JUnitStarter.main(JUnitStarter.java:53)
> 
> java.lang.ExceptionInInitializerError
> at com.tigerobo.javadl.Word2VecTest.nearestWords(Word2VecTest.java:30)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:50)
> at org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:12)
> at org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:47)
> at org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:17)
> at org.junit.runners.ParentRunner.runLeaf(ParentRunner.java:325)
> at org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:78)
> at org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:57)
> at org.junit.runners.ParentRunner$3.run(ParentRunner.java:290)
> at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:71)
> at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:288)
> at org.junit.runners.ParentRunner.access$000(ParentRunner.java:58)
> at org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:268)
> at org.junit.runners.ParentRunner.run(ParentRunner.java:363)
> at org.junit.runner.JUnitCore.run(JUnitCore.java:137)
> at com.intellij.junit4.JUnit4IdeaTestRunner.startRunnerWithArgs(JUnit4IdeaTestRunner.java:69)
> at com.intellij.rt.junit.IdeaTestRunner$Repeater.startRunnerWithArgs(IdeaTestRunner.java:33)
> at com.intellij.rt.junit.JUnitStarter.prepareStreamsAndStart(JUnitStarter.java:220)
> at com.intellij.rt.junit.JUnitStarter.main(JUnitStarter.java:53)
> Caused by: java.lang.RuntimeException: Unable to guess input file format. Please use corresponding loader directly
> at org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.readWord2VecModel(WordVectorSerializer.java:2416)
> at org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.readWord2VecModel(WordVectorSerializer.java:2372)
> at org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.readWord2VecModel(WordVectorSerializer.java:2341)
> at com.tigerobo.javadl.inference.Dl4jWord2VecInference.\<clinit\>(Dl4jWord2VecInference.java:23)
> ... 23 more
> \`
> \* pom.xml file or similar (also in a Gist)
> \`
> \<?xml version="1.0" encoding="UTF-8"?\>
> \<project xmlns="http://maven.apache.org/POM/4.0.0"
> xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
> xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"\>
> \<modelVersion\>4.0.0\</modelVersion\>
> 
> \<groupId\>com.tigerobo\</groupId\>
> \<artifactId\>javaDL\</artifactId\>
> \<version\>0.0.1-SNAPSHOT\</version\>
> 
> \<properties\>
> \<project.build.sourceEncoding\>UTF-8\</project.build.sourceEncoding\>
> \<maven.compiler.source\>1.8\</maven.compiler.source\>
> \<maven.compiler.target\>1.8\</maven.compiler.target\>
> 
> \<dl4j.version\>1.0.0-beta7\</dl4j.version\>
> \<djl.version\>0.8.0\</djl.version\>
> \</properties\>
> 
> \<parent\>
> \<groupId\>org.springframework.boot\</groupId\>
> \<artifactId\>spring-boot-parent\</artifactId\>
> \<version\>2.3.4.RELEASE\</version\>
> \</parent\>
> 
> \<dependencies\>
>         
> \<dependency\>
> \<groupId\>org.projectlombok\</groupId\>
> \<artifactId\>lombok\</artifactId\>
> \<version\>1.18.14\</version\>
> \</dependency\>
> \<dependency\>
> \<groupId\>org.apache.commons\</groupId\>
> \<artifactId\>commons-lang3\</artifactId\>
> \<version\>3.11\</version\>
> \</dependency\>
> \<dependency\>
> \<groupId\>commons-cli\</groupId\>
> \<artifactId\>commons-cli\</artifactId\>
> \<version\>1.4\</version\>
> \</dependency\>
> \<dependency\>
> \<groupId\>ch.qos.logback\</groupId\>
> \<artifactId\>logback-classic\</artifactId\>
> \<version\>1.2.3\</version\>
> \</dependency\>
> \<dependency\>
> \<groupId\>com.alibaba\</groupId\>
> \<artifactId\>fastjson\</artifactId\>
> \<version\>1.2.74\</version\>
> \</dependency\>
> \<dependency\>
> \<groupId\>junit\</groupId\>
> \<artifactId\>junit\</artifactId\>
> \<version\>4.12\</version\>
> \<scope\>test\</scope\>
> \</dependency\>
> 
>         
> \<dependency\>
> \<groupId\>ai.djl\</groupId\>
> \<artifactId\>model-zoo\</artifactId\>
> \<version\>${djl.version}\</version\>
> \</dependency\>
> \<dependency\>
> \<groupId\>ai.djl.mxnet\</groupId\>
> \<artifactId\>mxnet-model-zoo\</artifactId\>
> \<version\>${djl.version}\</version\>
> \</dependency\>
> \<dependency\>
> \<groupId\>ai.djl.mxnet\</groupId\>
> \<artifactId\>mxnet-native-auto\</artifactId\>
> \<version\>1.7.0-backport\</version\>
> \</dependency\>
> \<dependency\>
> \<groupId\>ai.djl.pytorch\</groupId\>
> \<artifactId\>pytorch-model-zoo\</artifactId\>
> \<version\>${djl.version}\</version\>
> \</dependency\>
> \<dependency\>
> \<groupId\>ai.djl.pytorch\</groupId\>
> \<artifactId\>pytorch-native-auto\</artifactId\>
> \<version\>1.6.0\</version\>
> \</dependency\>
> \<dependency\>
> \<groupId\>ai.djl.tensorflow\</groupId\>
> \<artifactId\>tensorflow-model-zoo\</artifactId\>
> \<version\>${djl.version}\</version\>
> \</dependency\>
> \<dependency\>
> \<groupId\>ai.djl.tensorflow\</groupId\>
> \<artifactId\>tensorflow-native-auto\</artifactId\>
> \<version\>2.3.0\</version\>
> \</dependency\>
> \<dependency\>
> \<groupId\>ai.djl\</groupId\>
> \<artifactId\>basicdataset\</artifactId\>
> \<version\>${djl.version}\</version\>
> \</dependency\>
> 
> \<dependency\>
> \<groupId\>org.deeplearning4j\</groupId\>
> \<artifactId\>deeplearning4j-nlp-chinese\</artifactId\>
> \<version\>${dl4j.version}\</version\>
> \</dependency\>
> \<dependency\>
> \<groupId\>org.nd4j\</groupId\>
> \<artifactId\>nd4j-native\</artifactId\>
> \<version\>${dl4j.version}\</version\>
> \</dependency\>
> \<dependency\>
> \<groupId\>org.nd4j\</groupId\>
> \<artifactId\>nd4j-native\</artifactId\>
> \<version\>${dl4j.version}\</version\>
> \<classifier\>macosx-x86\_64-avx2\</classifier\>
> \</dependency\>
> \<dependency\>
> \<groupId\>org.nd4j\</groupId\>
> \<artifactId\>nd4j-native\</artifactId\>
> \<version\>${dl4j.version}\</version\>
> \<classifier\>windows-x86\_64-avx2\</classifier\>
> \</dependency\>
> \</dependencies\>
> 
> \</project\>
> \`
> 
> \#### Contributing
> 
> If you'd like to help us fix the issue by contributing some code, but would
> like guidance or help in doing so, please mention it!
> I'm glad to do it!