How-to guide on Youtube

train.js is a script for kicking off a fine-tuning of a large language model using the Replicate API.

You can fine-tune your language model with your own training data and choose from one of the available models: Llama, GPT, and Flan.

You need:

• An account on Replicate
• Your Replicate API token
• A destination model to save your fine tuned model (Create a model)
• Training data in a .jsonl file, in the format: { prompt: "...", completion: "..." }
• A URL pointing to your generated training data

git clone https://github.com/fofr/replicate-llm-training
cd replicate-llm-training
npm install

Rename .env.example as .env and add your Replicate API token.

Open train.js and:

1. Set the destination variable to the username and model name you want to save the fine-tuned model to. For example, if your username is myusername and you want to save the model as mymodel, set destination to 'myusername/mymodel'.

2. Set the training_data_url variable to the URL of your training data.

3. Choose the pre-trained model you want to fine-tune. Use one of the following:

const [llm, version] = LLMs.llama // For Llama model
const [llm, version] = LLMs.gpt   // For GPT model
const [llm, version] = LLMs.flan  // For Flan model

After setting the variables, save the file and run the script with node train.js. The script will create a new fine-tuning job using the Replicate API, and it will print the details of the training job, including the URL to track the progress of your fine-tuning.

From the replicate.com dashboard you can:

• see the progress of your training
• view the logs
• cancel the training