list-language-models¶

Description¶

Provides a list of custom language models that match the specified criteria. If no criteria are specified, all language models are returned.

To get detailed information about a specific custom language model, use the operation.

Synopsis¶

  list-language-models
[--status-equals <value>]
[--name-contains <value>]
[--next-token <value>]
[--max-results <value>]
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]

Options¶

--status-equals (string)

Returns only custom language models with the specified status. Language models are ordered by creation date, with the newest model first. If you don’t include StatusEquals , all custom language models are returned.

Possible values:

IN_PROGRESS

FAILED

COMPLETED

--name-contains (string)

Returns only the custom language models that contain the specified string. The search is not case sensitive.

--next-token (string)

If your ListLanguageModels request returns more results than can be displayed, NextToken is displayed in the response with an associated string. To get the next page of results, copy this string and repeat your request, including NextToken with the value of the copied string. Repeat as needed to view all your results.

--max-results (integer)

The maximum number of custom language models to return in each page of results. If there are fewer results than the value you specify, only the actual results are returned. If you don’t specify a value, a default of 5 is used.

--cli-input-json | --cli-input-yaml (string) Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command. The generated JSON skeleton is not stable between versions of the AWS CLI and there are no backwards compatibility guarantees in the JSON skeleton generated.

See ‘aws help’ for descriptions of global parameters.

Examples¶

Note

To use the following examples, you must have the AWS CLI installed and configured. See the Getting started guide in the AWS CLI User Guide for more information.

Unless otherwise stated, all examples have unix-like quotation rules. These examples will need to be adapted to your terminal’s quoting rules. See Using quotation marks with strings in the AWS CLI User Guide .

To list your custom language models

The following list-language-models example lists the custom language models associated with your AWS account and Region. You can use the S3Uri and TuningDataS3Uri parameters to find the Amazon S3 prefixes you’ve used as your training data, or your tuning data. The BaseModelName tells you whether you’ve used a NarrowBand, or WideBand model to create a custom language model. You can transcribe audio with a sample rate of less than 16 kHz with a custom language model using a NarrowBand base model. You can transcribe audio 16 kHz or greater with a custom language model using a WideBand base model. The ModelStatus parameter shows whether you can use the custom language model in a transcription job. If the value is COMPLETED, you can use it in a transcription job.

aws transcribe list-language-models

Output:

{
    "Models": [
        {
            "ModelName": "cli-clm-2",
            "CreateTime": "2020-09-25T17:57:38.504000+00:00",
            "LastModifiedTime": "2020-09-25T17:57:48.585000+00:00",
            "LanguageCode": "language-code",
            "BaseModelName": "WideBand",
            "ModelStatus": "IN_PROGRESS",
            "UpgradeAvailability": false,
            "InputDataConfig": {
                "S3Uri": "s3://DOC-EXAMPLE-BUCKET/clm-training-data/",
                "TuningDataS3Uri": "s3://DOC-EXAMPLE-BUCKET/clm-tuning-data/",
                "DataAccessRoleArn": "arn:aws:iam::AWS-account-number:role/IAM-role-used-to-create-the-custom-language-model"
            }
        },
        {
            "ModelName": "cli-clm-1",
            "CreateTime": "2020-09-25T17:16:01.835000+00:00",
            "LastModifiedTime": "2020-09-25T17:16:15.555000+00:00",
            "LanguageCode": "language-code",
            "BaseModelName": "WideBand",
            "ModelStatus": "IN_PROGRESS",
            "UpgradeAvailability": false,
            "InputDataConfig": {
                "S3Uri": "s3://DOC-EXAMPLE-BUCKET/clm-training-data/",
                "DataAccessRoleArn": "arn:aws:iam::AWS-account-number:role/IAM-role-used-to-create-the-custom-language-model"
            }
        },
        {
            "ModelName": "clm-console-1",
            "CreateTime": "2020-09-24T19:26:28.076000+00:00",
            "LastModifiedTime": "2020-09-25T04:25:22.271000+00:00",
            "LanguageCode": "language-code",
            "BaseModelName": "NarrowBand",
            "ModelStatus": "COMPLETED",
            "UpgradeAvailability": false,
            "InputDataConfig": {
                "S3Uri": "s3://DOC-EXAMPLE-BUCKET/clm-training-data/",
                "DataAccessRoleArn": "arn:aws:iam::AWS-account-number:role/IAM-role-used-to-create-the-custom-language-model"
            }
        }
    ]
}

For more information, see Improving Domain-Specific Transcription Accuracy with Custom Language Models in the Amazon Transcribe Developer Guide.

Output¶

NextToken -> (string)

If NextToken is present in your response, it indicates that not all results are displayed. To view the next set of results, copy the string associated with the NextToken parameter in your results output, then run your request again including NextToken with the value of the copied string. Repeat as needed to view all your results.

Models -> (list)

Provides information about the custom language models that match the criteria specified in your request.

(structure)

Provides information about a custom language model, including the base model name, when the model was created, the location of the files used to train the model, when the model was last modified, the name you chose for the model, its language, its processing state, and if there is an upgrade available for the base model.

ModelName -> (string)

A unique name, chosen by you, for your custom language model.

This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account.

CreateTime -> (timestamp)

The date and time the specified custom language model was created.

Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC . For example, 2022-05-04T12:32:58.761000-07:00 represents 12:32 PM UTC-7 on May 4, 2022.

LastModifiedTime -> (timestamp)

The date and time the specified language model was last modified.

Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC . For example, 2022-05-04T12:32:58.761000-07:00 represents 12:32 PM UTC-7 on May 4, 2022.

LanguageCode -> (string)

The language code used to create your custom language model. Each language model must contain terms in only one language, and the language you select for your model must match the language of your training and tuning data.

For a list of supported languages and their associated language codes, refer to the Supported languages table. Note that U.S. English (en-US ) is the only language supported with Amazon Transcribe Medical.

BaseModelName -> (string)

The Amazon Transcribe standard language model, or base model, used to create your custom language model.

ModelStatus -> (string)

The status of the specified custom language model. When the status displays as COMPLETED the model is ready for use.

UpgradeAvailability -> (boolean)

Shows if a more current base model is available for use with the specified custom language model.

If false , your language model is using the most up-to-date base model.

If true , there is a newer base model available than the one your language model is using.

Note that to update a base model, you must recreate the custom language model using the new base model. Base model upgrades for existing custom language models are not supported.

FailureReason -> (string)

If ModelStatus is FAILED , FailureReason contains information about why the custom language model request failed. See also: Common Errors .

InputDataConfig -> (structure)

The Amazon S3 location of the input files used to train and tune your custom language model, in addition to the data access role ARN (Amazon Resource Name) that has permissions to access these data.

S3Uri -> (string)

The Amazon S3 location (URI) of the text files you want to use to train your custom language model.

Here’s an example URI path: s3://DOC-EXAMPLE-BUCKET/my-model-training-data/

TuningDataS3Uri -> (string)

The Amazon S3 location (URI) of the text files you want to use to tune your custom language model.

Here’s an example URI path: s3://DOC-EXAMPLE-BUCKET/my-model-tuning-data/

DataAccessRoleArn -> (string)

The Amazon Resource Name (ARN) of an IAM role that has permissions to access the Amazon S3 bucket that contains your input files. If the role you specify doesn’t have the appropriate permissions to access the specified Amazon S3 location, your request fails.

IAM role ARNs have the format arn:partition:iam::account:role/role-name-with-path . For example: arn:aws:iam::111122223333:role/Admin .

For more information, see IAM ARNs .

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