38 lines
934 B
Markdown
38 lines
934 B
Markdown
# Model Tuning
|
|
|
|
Supervised Fine-Tuning or Preference Tuning using your own datasets.
|
|
|
|
```python
|
|
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)
|
|
```
|