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  • Bakery Docs
    • Getting Started with the Bakery
    • Creating and Managing API Keys
    • Creating Datasets and Models
    • Uploading Files to the Bakery
    • Fine-Tuning Using The Bakery: Step-by-Step Guide
    • Purchasing and Publishing Assets to Marketplace
    • HuggingFace Integration Guide
  • Bagel Packages
    • Bagel Python Package
      • Bagels RAW - finetuning asset Quickstart.md
      • Fine-Tuning AI Models with Bagel - Overview
      • Fine-tuning LLama3 Models on Bagel
    • Bagel JavaScript Package
      • QuickStart
      • Fine-Tuning AI Models
  • Dataset Preparation Guide for Fine-tuning
  • Supported LLM Models for Fine-tuning in Bakery
  • How to Fine-tune LLM Successfully in Bakery
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  • Step 1: Creating Your Raw Fine-Tuning Dataset
  • Step 2: Fine-Tuning Your Model
  • Final Step: Downloading the Fine-Tuned Model
  1. Bakery Docs

Fine-Tuning Using The Bakery: Step-by-Step Guide

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Last updated 5 months ago

This guide will walk you through the process of fine-tuning a model using datasets in The Bakery.

Step 1: Creating Your Raw Fine-Tuning Dataset

Start by navigating to the top of your screen and selecting Create Dataset.

Next, choose a name for your dataset, assign a category and tags, and select Raw Dataset as the dataset type.

A raw dataset contains unprocessed data that will be used to train and fine-tune your model. Unlike a vector dataset, which is optimized for querying or searching, raw datasets are essential for fine-tuning because they contain detailed training data without any preprocessing.

Once the dataset is created, it will be labeled with the special identifier RAW.

Now, navigate to the newly created dataset and upload the file for the fine-tuning process. In this example, we are using a file in Parquet format.

Step 2: Fine-Tuning Your Model

While in the Files section, locate the Fine Tune option on the right-hand side of your screen.

Create a name for the fine-tuned model.

Next, select the Base Model from my models.

Next, select the Raw Dataset we created earlier, which should contain the training data.

Choose the file from the Raw Dataset that you want to use for training.

Select GPU from available options

Next, select appropriate Epochs & Learning Rate for proper fine-tuning

After you’ve submitted your inputs, click Confirm Fine Tune and proceed with the transaction for the fine-tuning process.

A progress bar will appear, allowing you to monitor the fine-tuning process.

Also, you can check check training progress logs from "Logs" option

Final Step: Downloading the Fine-Tuned Model

Once the fine-tuning is complete, you can download the fine-tuned model files by navigating to the Files section and selecting Download All.

Need extra help or just want to connect with other developers? Join our community on Discord for additional support (https://discord.gg/bagelnet) 👾

You can now begin the fine-tuning process by filling in the required details. For this tutorial, we’ll be using a base model from the marketplace. For more information on purchasing and listing models or datasets on The Bakery, refer to the .

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