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The command llmtune inference [experiment_dir] aims to provide a versatile interface for running inference on pre-trained language models, allowing users to:
Load and run inference on a dataset; or
Provide arbitrary text inputs for inference for spot checks; or
Specify specific inputs to be injected in prompt template for inference
Proposed CLI
llmtune inference [experiment_dir] [options]
Arguments
experiment_dir: The experiment directory from finetuning experiments
Options
--dataset [dataset_path]: Path to a dataset (e.g., CSV, JSON, or Huggingface) --text-input [text]: An arbitrary text input to run inference on. This option can be used for a single text input or for quick manual inference. --column [name=value]: Allows specification of a column name and value for custom inputs. This option can be used multiple times to specify different column values.
The command
llmtune inference [experiment_dir]
aims to provide a versatile interface for running inference on pre-trained language models, allowing users to:Proposed CLI
llmtune inference [experiment_dir] [options]
Arguments
experiment_dir
: The experiment directory from finetuning experimentsOptions
--dataset [dataset_path]
: Path to a dataset (e.g., CSV, JSON, or Huggingface)--text-input [text]
: An arbitrary text input to run inference on. This option can be used for a single text input or for quick manual inference.--column [name=value]
: Allows specification of a column name and value for custom inputs. This option can be used multiple times to specify different column values.Examples
Inference on a dataset:
Inference on arbitrary text:
llmtune inference ./my_experiment --text-input "This is an example text input for inference."
Inference with specific input values:
Related to: #160
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