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Version: 25.1

snorkelflow.sdk.ExternalModel

class snorkelflow.sdk.ExternalModel(external_model_name, column_mappings={'context': FineTuningColumnType.CONTEXT, 'instruction': FineTuningColumnType.INSTRUCTION, 'prompt_prefix': FineTuningColumnType.PROMPT_PREFIX, 'response': FineTuningColumnType.RESPONSE}, finetuning_provider_type=FinetuningProvider.AWS_SAGEMAKER)

Bases: object

__init__​

__init__(external_model_name, column_mappings={'context': FineTuningColumnType.CONTEXT, 'instruction': FineTuningColumnType.INSTRUCTION, 'prompt_prefix': FineTuningColumnType.PROMPT_PREFIX, 'response': FineTuningColumnType.RESPONSE}, finetuning_provider_type=FinetuningProvider.AWS_SAGEMAKER)

Class to represent a trained 3rd party model. Returns from ExternalModelTrainer.finetune

Parameters​

NameTypeDefaultInfo
external_model_namestrThe name generated by the external model finetuning job.
column_mappingsDict[str, FineTuningColumnType]{'instruction': <FineTuningColumnType.INSTRUCTION: 'instruction'>, 'context': <FineTuningColumnType.CONTEXT: 'context'>, 'response': <FineTuningColumnType.RESPONSE: 'response'>, 'prompt_prefix': <FineTuningColumnType.PROMPT_PREFIX: 'prompt_prefix'>}The column mappings from the dataset’s columns to the standard finetuning columns.
finetuning_provider_typeFinetuningProvider<FinetuningProvider.AWS_SAGEMAKER: 'sagemaker'>The 3rd party training service. Defaults to FinetuningProvider.AWS_SAGEMAKER.

Methods

__init__(external_model_name[, ...])

Class to represent a trained 3rd party model.

inference(datasource_uids[, x_uids, ...])

3rd Party Inference using the finetuned model.

inference​

inference(datasource_uids, x_uids=None, generation_config=None, deployment_config=None, prompt_template=None, sync=True)

3rd Party Inference using the finetuned model.

Parameters​

NameTypeDefaultInfo
datasource_uidsList[int]The datasource uids to use for inference.
x_uidsOptional[List[str]]NoneOptional x_uids for filtering the datasources.
generation_configOptional[Dict[str, Any]]None

Optional generation configuration, e.g.:

{
    "max_new_tokens": 300,
    "top_k": 50,
    "top_p": 0.8,
    "do_sample": True,
    "temperature": 1,
}
deployment_configOptional[Dict[str, Any]]None

Optional deployment configuration e.g.:

{
    "instance_type": "ml.g5.12xlarge",
    "instance_count": 1,
}
prompt_templateOptional[str]NoneOptional prompt template to LLM inference. Defaults to {instruction}
syncboolTrueWhether to wait for the inference job to complete before returning.

Returns​

if (sync=True) returns the model source uid, else returns the job id

Return type​

str