// Copyright 2024 Google LLC // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. syntax = "proto3"; package google.ai.generativelanguage.v1beta3; import "google/api/field_behavior.proto"; import "google/api/resource.proto"; import "google/protobuf/timestamp.proto"; option go_package = "cloud.google.com/go/ai/generativelanguage/apiv1beta3/generativelanguagepb;generativelanguagepb"; option java_multiple_files = true; option java_outer_classname = "TunedModelProto"; option java_package = "com.google.ai.generativelanguage.v1beta3"; // A fine-tuned model created using ModelService.CreateTunedModel. message TunedModel { option (google.api.resource) = { type: "generativelanguage.googleapis.com/TunedModel" pattern: "tunedModels/{tuned_model}" plural: "tunedModels" singular: "tunedModel" }; // The state of the tuned model. enum State { // The default value. This value is unused. STATE_UNSPECIFIED = 0; // The model is being created. CREATING = 1; // The model is ready to be used. ACTIVE = 2; // The model failed to be created. FAILED = 3; } // The model used as the starting point for tuning. oneof source_model { // Optional. TunedModel to use as the starting point for training the new // model. TunedModelSource tuned_model_source = 3 [(google.api.field_behavior) = OPTIONAL]; // Immutable. The name of the `Model` to tune. // Example: `models/text-bison-001` string base_model = 4 [ (google.api.field_behavior) = IMMUTABLE, (google.api.resource_reference) = { type: "generativelanguage.googleapis.com/Model" } ]; } // Output only. The tuned model name. A unique name will be generated on // create. Example: `tunedModels/az2mb0bpw6i` If display_name is set on // create, the id portion of the name will be set by concatenating the words // of the display_name with hyphens and adding a random portion for // uniqueness. Example: // display_name = "Sentence Translator" // name = "tunedModels/sentence-translator-u3b7m" string name = 1 [(google.api.field_behavior) = OUTPUT_ONLY]; // Optional. The name to display for this model in user interfaces. // The display name must be up to 40 characters including spaces. string display_name = 5 [(google.api.field_behavior) = OPTIONAL]; // Optional. A short description of this model. string description = 6 [(google.api.field_behavior) = OPTIONAL]; // Optional. Controls the randomness of the output. // // Values can range over `[0.0,1.0]`, inclusive. A value closer to `1.0` will // produce responses that are more varied, while a value closer to `0.0` will // typically result in less surprising responses from the model. // // This value specifies default to be the one used by the base model while // creating the model. optional float temperature = 11 [(google.api.field_behavior) = OPTIONAL]; // Optional. For Nucleus sampling. // // Nucleus sampling considers the smallest set of tokens whose probability // sum is at least `top_p`. // // This value specifies default to be the one used by the base model while // creating the model. optional float top_p = 12 [(google.api.field_behavior) = OPTIONAL]; // Optional. For Top-k sampling. // // Top-k sampling considers the set of `top_k` most probable tokens. // This value specifies default to be used by the backend while making the // call to the model. // // This value specifies default to be the one used by the base model while // creating the model. optional int32 top_k = 13 [(google.api.field_behavior) = OPTIONAL]; // Output only. The state of the tuned model. State state = 7 [(google.api.field_behavior) = OUTPUT_ONLY]; // Output only. The timestamp when this model was created. google.protobuf.Timestamp create_time = 8 [(google.api.field_behavior) = OUTPUT_ONLY]; // Output only. The timestamp when this model was updated. google.protobuf.Timestamp update_time = 9 [(google.api.field_behavior) = OUTPUT_ONLY]; // Required. The tuning task that creates the tuned model. TuningTask tuning_task = 10 [(google.api.field_behavior) = REQUIRED]; } // Tuned model as a source for training a new model. message TunedModelSource { // Immutable. The name of the `TunedModel` to use as the starting point for // training the new model. // Example: `tunedModels/my-tuned-model` string tuned_model = 1 [ (google.api.field_behavior) = IMMUTABLE, (google.api.resource_reference) = { type: "generativelanguage.googleapis.com/TunedModel" } ]; // Output only. The name of the base `Model` this `TunedModel` was tuned from. // Example: `models/text-bison-001` string base_model = 2 [ (google.api.field_behavior) = OUTPUT_ONLY, (google.api.resource_reference) = { type: "generativelanguage.googleapis.com/Model" } ]; } // Tuning tasks that create tuned models. message TuningTask { // Output only. The timestamp when tuning this model started. google.protobuf.Timestamp start_time = 1 [(google.api.field_behavior) = OUTPUT_ONLY]; // Output only. The timestamp when tuning this model completed. google.protobuf.Timestamp complete_time = 2 [(google.api.field_behavior) = OUTPUT_ONLY]; // Output only. Metrics collected during tuning. repeated TuningSnapshot snapshots = 3 [(google.api.field_behavior) = OUTPUT_ONLY]; // Required. Input only. Immutable. The model training data. Dataset training_data = 4 [ (google.api.field_behavior) = INPUT_ONLY, (google.api.field_behavior) = REQUIRED, (google.api.field_behavior) = IMMUTABLE ]; // Immutable. Hyperparameters controlling the tuning process. If not provided, // default values will be used. Hyperparameters hyperparameters = 5 [(google.api.field_behavior) = IMMUTABLE]; } // Hyperparameters controlling the tuning process. message Hyperparameters { // Immutable. The number of training epochs. An epoch is one pass through the // training data. If not set, a default of 10 will be used. optional int32 epoch_count = 14 [(google.api.field_behavior) = IMMUTABLE]; // Immutable. The batch size hyperparameter for tuning. // If not set, a default of 16 or 64 will be used based on the number of // training examples. optional int32 batch_size = 15 [(google.api.field_behavior) = IMMUTABLE]; // Immutable. The learning rate hyperparameter for tuning. // If not set, a default of 0.0002 or 0.002 will be calculated based on the // number of training examples. optional float learning_rate = 16 [(google.api.field_behavior) = IMMUTABLE]; } // Dataset for training or validation. message Dataset { // Inline data or a reference to the data. oneof dataset { // Optional. Inline examples. TuningExamples examples = 1 [(google.api.field_behavior) = OPTIONAL]; } } // A set of tuning examples. Can be training or validatation data. message TuningExamples { // Required. The examples. Example input can be for text or discuss, but all // examples in a set must be of the same type. repeated TuningExample examples = 1 [(google.api.field_behavior) = REQUIRED]; } // A single example for tuning. message TuningExample { // The input to the model for this example. oneof model_input { // Optional. Text model input. string text_input = 1 [(google.api.field_behavior) = OPTIONAL]; } // Required. The expected model output. string output = 3 [(google.api.field_behavior) = REQUIRED]; } // Record for a single tuning step. message TuningSnapshot { // Output only. The tuning step. int32 step = 1 [(google.api.field_behavior) = OUTPUT_ONLY]; // Output only. The epoch this step was part of. int32 epoch = 2 [(google.api.field_behavior) = OUTPUT_ONLY]; // Output only. The mean loss of the training examples for this step. float mean_loss = 3 [(google.api.field_behavior) = OUTPUT_ONLY]; // Output only. The timestamp when this metric was computed. google.protobuf.Timestamp compute_time = 4 [(google.api.field_behavior) = OUTPUT_ONLY]; }