Starting April 29, 2025, Gemini 1.5 Pro and Gemini 1.5 Flash models are not available in projects that have no prior usage of these models, including new projects. For details, see Model versions and lifecycle
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Fine-tune Generative AI models with Vertex AI Supervised Fine-tuning
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Automatically tune a Gemini model using Google Cloud's Vertex AI SFT (Supervised Fine-tuning).
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For detailed documentation that includes this code sample, see the following:
Code sample
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[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],[],[],[],null,["# Fine-tune Generative AI models with Vertex AI Supervised Fine-tuning\n\nAutomatically tune a Gemini model using Google Cloud's Vertex AI SFT (Supervised Fine-tuning).\n\nExplore further\n---------------\n\n\nFor detailed documentation that includes this code sample, see the following:\n\n- [Tune Gemini models by using supervised fine-tuning](/vertex-ai/generative-ai/docs/models/gemini-use-supervised-tuning)\n- [Tuning API](/vertex-ai/generative-ai/docs/model-reference/tuning)\n\nCode sample\n-----------\n\n### Python\n\n\nBefore trying this sample, follow the Python setup instructions in the\n[Vertex AI quickstart using\nclient libraries](/vertex-ai/docs/start/client-libraries).\n\n\nFor more information, see the\n[Vertex AI Python API\nreference documentation](/python/docs/reference/aiplatform/latest).\n\n\nTo authenticate to Vertex AI, set up Application Default Credentials.\nFor more information, see\n\n[Set up authentication for a local development environment](/docs/authentication/set-up-adc-local-dev-environment).\n\n\n import time\n\n import https://cloud.google.com/python/docs/reference/vertexai/latest/\n from vertexai.tuning import https://cloud.google.com/python/docs/reference/vertexai/latest/vertexai.preview.tuning.sft.html\n\n # TODO(developer): Update and un-comment below line\n # PROJECT_ID = \"your-project-id\"\n https://cloud.google.com/python/docs/reference/vertexai/latest/.init(project=PROJECT_ID, location=\"us-central1\")\n\n sft_tuning_job = https://cloud.google.com/python/docs/reference/vertexai/latest/vertexai.preview.tuning.sft.html.https://cloud.google.com/python/docs/reference/vertexai/latest/vertexai.preview.tuning.sft.html(\n source_model=\"gemini-2.0-flash-001\",\n # 1.5 and 2.0 models use the same JSONL format\n train_dataset=\"gs://cloud-samples-data/ai-platform/generative_ai/gemini-1_5/text/sft_train_data.jsonl\",\n )\n\n # Polling for job completion\n while not sft_tuning_job.has_ended:\n time.sleep(60)\n sft_tuning_job.refresh()\n\n print(sft_tuning_job.tuned_model_name)\n print(sft_tuning_job.tuned_model_endpoint_name)\n print(sft_tuning_job.experiment)\n # Example response:\n # projects/123456789012/locations/us-central1/models/1234567890@1\n # projects/123456789012/locations/us-central1/endpoints/123456789012345\n # \u003cgoogle.cloud.aiplatform.metadata.experiment_resources.Experiment object at 0x7b5b4ae07af0\u003e\n\nWhat's next\n-----------\n\n\nTo search and filter code samples for other Google Cloud products, see the\n[Google Cloud sample browser](/docs/samples?product=generativeaionvertexai)."]]
