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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)."]]