Model Tuning
Supervised Fine-Tuning or Preference Tuning using your own datasets.
import time
from google import genai
from google.genai import types
client = genai.Client()
training_dataset = types.TuningDataset(
gcs_uri="gs://your-bucket/sft_train_data.jsonl",
)
tuning_job = client.tunings.tune(
base_model="gemini-3-flash-preview",
training_dataset=training_dataset,
config=types.CreateTuningJobConfig(
tuned_model_display_name="Example tuning job",
),
)
running_states = {"JOB_STATE_PENDING", "JOB_STATE_RUNNING"}
while tuning_job.state in running_states:
time.sleep(60)
tuning_job = client.tunings.get(name=tuning_job.name)
print("Tuned Model Endpoint:", tuning_job.tuned_model.endpoint)
# Predict with the tuned endpoint
response = client.models.generate_content(
model=tuning_job.tuned_model.endpoint,
contents="Why is the sky blue?",
)
print(response.text)