Mulai 29 April 2025, model Gemini 1.5 Pro dan Gemini 1.5 Flash tidak tersedia di project yang belum pernah menggunakan model ini, termasuk project baru. Untuk mengetahui detailnya, lihat
Versi dan siklus proses model.
Meningkatkan kualitas model AI Generatif dengan Penyesuaian Terpantau Vertex AI
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Simpan dan kategorikan konten berdasarkan preferensi Anda.
Menyesuaikan model Gemini secara otomatis menggunakan SFT (Supervised Fine-tuning) Vertex AI Google Cloud.
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Untuk dokumentasi mendetail yang menyertakan contoh kode ini, lihat artikel berikut:
Contoh kode
Kecuali dinyatakan lain, konten di halaman ini dilisensikan berdasarkan Lisensi Creative Commons Attribution 4.0, sedangkan contoh kode dilisensikan berdasarkan Lisensi Apache 2.0. Untuk mengetahui informasi selengkapnya, lihat Kebijakan Situs Google Developers. Java adalah merek dagang terdaftar dari Oracle dan/atau afiliasinya.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","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)."]]
