Fine-Tune

In the following guide, we'll learn how to use the Yotta AI fine-tuning CLI tool to fine-tune a Llama 3 7B model on a testing dataset.

Install the CLI

To get started, install the Yotta Python CLI:

pip install --upgrade yotta

Authentication

The API Key can be configured via setting the YOTTA_API_KEY environment variable by running the following command:

export YOTTA_API_KEY=xxxxx

Uploading Data

To upload your data, run the following command. Remember to replace PATH_TO_DATA_FILE with the path to your dataset.

yotta files upload {PATH_TO_DATA_FILE}

Start Fine-Tuning Job

You now can start the fine-tuning job based on your training file and model. The command line is:

yotta fine-tuning start --training-file {FILE_ID} --model {MODEL_NAME} --wandb-api-key {WANDB_API_KEY}

Monitor Jobs

You can use the following command line to get the progress of a job:

yotta fine-tuning list-events {FINE-TUNING_ID}

Other Useful CLI Commands

# list all available commands
yotta --help

# check which models are available.
yotta models list

# check your jsonl file
yotta files check test.jsonl

# upload your jsonl file
yotta files upload test.jsonl

# list your uploaded files
yotta files list

# retrieve progress updates about the finetune job
yotta fine-tuning retrieve ft-01b7df2b-122a-4b84-9838-4d84200dc7ac

# download your fine-tuned model using the uuid of your fine-tuning job
yotta fine-tuning download ft-01b7df2b-122a-4b84-9838-4d84200dc7ac 

Pricing