Foundation Models Tuning Service API, gRPC: TuningService.GetOptions

{
  "task_id": "string"
}

{
  "task_id": "string",
  "base_model_uri": "string",
  "train_datasets": [
    {
      "dataset_id": "string",
      "weight": "double"
    }
  ],
  "validation_datasets": [
    {
      "dataset_id": "string",
      "weight": "double"
    }
  ],
  // Includes only one of the fields `text_to_text_completion`, `text_classification_multilabel`, `text_classification_multiclass`, `text_embedding_pair_params`, `text_embedding_triplet_params`
  "text_to_text_completion": {
    "seed": "int64",
    "lr": "double",
    "n_samples": "int64",
    "additional_arguments": "string",
    // Includes only one of the fields `lora`, `prompt_tune`
    "lora": {
      "rank": "int64",
      "alpha": "double",
      "initialization": "string",
      "type": "string"
    },
    "prompt_tune": {
      "virtual_tokens": "int64"
    },
    // end of the list of possible fields
    "scheduler": {
      // Includes only one of the fields `linear`, `constant`, `cosine`
      "linear": {
        "min_lr": "double"
      },
      "constant": "SchedulerConstant",
      "cosine": {
        "min_lr": "double"
      },
      // end of the list of possible fields
      "warmup_ratio": "double"
    },
    "optimizer": {
      // Includes only one of the fields `adamw`
      "adamw": {
        "beta1": "double",
        "beta2": "double",
        "eps": "double",
        "weight_decay": "double"
      }
      // end of the list of possible fields
    }
  },
  "text_classification_multilabel": {
    "seed": "int64",
    "lr": "double",
    "n_samples": "int64",
    "additional_arguments": "string",
    // Includes only one of the fields `lora`, `prompt_tune`
    "lora": {
      "rank": "int64",
      "alpha": "double",
      "initialization": "string",
      "type": "string"
    },
    "prompt_tune": {
      "virtual_tokens": "int64"
    },
    // end of the list of possible fields
    "scheduler": {
      // Includes only one of the fields `linear`, `constant`, `cosine`
      "linear": {
        "min_lr": "double"
      },
      "constant": "SchedulerConstant",
      "cosine": {
        "min_lr": "double"
      },
      // end of the list of possible fields
      "warmup_ratio": "double"
    },
    "optimizer": {
      // Includes only one of the fields `adamw`
      "adamw": {
        "beta1": "double",
        "beta2": "double",
        "eps": "double",
        "weight_decay": "double"
      }
      // end of the list of possible fields
    }
  },
  "text_classification_multiclass": {
    "seed": "int64",
    "lr": "double",
    "n_samples": "int64",
    "additional_arguments": "string",
    // Includes only one of the fields `lora`, `prompt_tune`
    "lora": {
      "rank": "int64",
      "alpha": "double",
      "initialization": "string",
      "type": "string"
    },
    "prompt_tune": {
      "virtual_tokens": "int64"
    },
    // end of the list of possible fields
    "scheduler": {
      // Includes only one of the fields `linear`, `constant`, `cosine`
      "linear": {
        "min_lr": "double"
      },
      "constant": "SchedulerConstant",
      "cosine": {
        "min_lr": "double"
      },
      // end of the list of possible fields
      "warmup_ratio": "double"
    },
    "optimizer": {
      // Includes only one of the fields `adamw`
      "adamw": {
        "beta1": "double",
        "beta2": "double",
        "eps": "double",
        "weight_decay": "double"
      }
      // end of the list of possible fields
    }
  },
  "text_embedding_pair_params": {
    "seed": "int64",
    "lr": "double",
    "n_samples": "int64",
    "additional_arguments": "string",
    "embedding_dims": [
      "int64"
    ],
    // Includes only one of the fields `lora`, `prompt_tune`
    "lora": {
      "rank": "int64",
      "alpha": "double",
      "initialization": "string",
      "type": "string"
    },
    "prompt_tune": {
      "virtual_tokens": "int64"
    },
    // end of the list of possible fields
    "scheduler": {
      // Includes only one of the fields `linear`, `constant`, `cosine`
      "linear": {
        "min_lr": "double"
      },
      "constant": "SchedulerConstant",
      "cosine": {
        "min_lr": "double"
      },
      // end of the list of possible fields
      // Includes only one of the fields `warmup_ratio`
      "warmup_ratio": "double"
      // end of the list of possible fields
    },
    "optimizer": {
      // Includes only one of the fields `adamw`
      "adamw": {
        "beta1": "double",
        "beta2": "double",
        "eps": "double",
        "weight_decay": "double"
      }
      // end of the list of possible fields
    }
  },
  "text_embedding_triplet_params": {
    "seed": "int64",
    "lr": "double",
    "n_samples": "int64",
    "additional_arguments": "string",
    "embedding_dims": [
      "int64"
    ],
    // Includes only one of the fields `lora`, `prompt_tune`
    "lora": {
      "rank": "int64",
      "alpha": "double",
      "initialization": "string",
      "type": "string"
    },
    "prompt_tune": {
      "virtual_tokens": "int64"
    },
    // end of the list of possible fields
    "scheduler": {
      // Includes only one of the fields `linear`, `constant`, `cosine`
      "linear": {
        "min_lr": "double"
      },
      "constant": "SchedulerConstant",
      "cosine": {
        "min_lr": "double"
      },
      // end of the list of possible fields
      // Includes only one of the fields `warmup_ratio`
      "warmup_ratio": "double"
      // end of the list of possible fields
    },
    "optimizer": {
      // Includes only one of the fields `adamw`
      "adamw": {
        "beta1": "double",
        "beta2": "double",
        "eps": "double",
        "weight_decay": "double"
      }
      // end of the list of possible fields
    }
  }
  // end of the list of possible fields
}