model_tuning

Supervised Fine-Tuning or Preference Tuning using your own datasets.

Skills
AI research
1

What it does and how to use it

A skill that teaches Claude Code to do ai research tasks well. It is packaged knowledge the model uses whenever it is relevant.

Install the skill (command above).
In Claude Code, describe what you need - the skill turns on by itself when the context fits.
No commands to memorize: you talk in plain language and the skill does the rest.

Install (Claude Code)

mkdir -p .claude/skills/model-tuning && curl -fsSL https://doutorai.pt/data/lib/skills__model-tuning.md -o .claude/skills/model-tuning/SKILL.md

Paste this command into the terminal, in your project folder, and the component installs automatically.

Content

# 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_s

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