public class CreateModelOptions
extends com.ibm.cloud.sdk.core.service.model.GenericModel
Modifier and Type | Class and Description |
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static class |
CreateModelOptions.Builder
Builder.
|
Modifier and Type | Field and Description |
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protected java.lang.String |
baseModelId |
protected java.io.InputStream |
forcedGlossary |
protected java.lang.String |
name |
protected java.io.InputStream |
parallelCorpus |
Modifier | Constructor and Description |
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protected |
CreateModelOptions(CreateModelOptions.Builder builder) |
Modifier and Type | Method and Description |
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java.lang.String |
baseModelId()
Gets the baseModelId.
|
java.io.InputStream |
forcedGlossary()
Gets the forcedGlossary.
|
java.lang.String |
name()
Gets the name.
|
CreateModelOptions.Builder |
newBuilder()
New builder.
|
java.io.InputStream |
parallelCorpus()
Gets the parallelCorpus.
|
protected java.lang.String baseModelId
protected java.io.InputStream forcedGlossary
protected java.io.InputStream parallelCorpus
protected java.lang.String name
protected CreateModelOptions(CreateModelOptions.Builder builder)
public CreateModelOptions.Builder newBuilder()
public java.lang.String baseModelId()
The model ID of the model to use as the base for customization. To see available models, use the `List models` method. Usually all IBM provided models are customizable. In addition, all your models that have been created via parallel corpus customization, can be further customized with a forced glossary.
public java.io.InputStream forcedGlossary()
A TMX file with your customizations. The customizations in the file completely overwrite the domain translaton data, including high frequency or high confidence phrase translations. You can upload only one glossary with a file size less than 10 MB per call. A forced glossary should contain single words or short phrases.
public java.io.InputStream parallelCorpus()
A TMX file with parallel sentences for source and target language. You can upload multiple parallel_corpus files in one request. All uploaded parallel_corpus files combined, your parallel corpus must contain at least 5,000 parallel sentences to train successfully.
public java.lang.String name()
An optional model name that you can use to identify the model. Valid characters are letters, numbers, dashes, underscores, spaces and apostrophes. The maximum length is 32 characters.