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Fine-tune a Large Language Model (LLM)

This guide walks you through the process of fine-tuning a large language model using MonsterTuner - a no code scalable LLM fine-tuner

Welcome to our guide for fine-tuning LLMs! Here you'll find comprehensive walkthroughs that'll assist you with launching, tracking, and understanding the billing process related to the fine-tuning of Large Language Models (LLMs) on MonsterAPI Platform.

Below, you'll find a brief description of the three pages that provide essential information about each step of the process.

This guide will walk you through step-by-step on how to initiate a fine-tuning job for an LLM. From opening the fine-tuning portal and creating a new job, to choosing a model and dataset preparation, and finally submitting your job. The guide covers all steps in detail, ensuring you have all the tools and information necessary to successfully launch a fine-tuning job.

Dataset needs to be prepared in the right format for ensuring that the model learns the right values and parameters. Thus, we provide a text-area while creating a fine-tuning job in which target columns can be specified. Depending on the type of task chosen, you may have to alter the column names. Refer to dataset preparation doc for examples.

Once your fine-tuning job is launched, it's essential to monitor its progress. This page helps you understand the different stages a job goes through, from launching to completion. You'll also learn how to view job logs, monitor your job metrics using Weights & Biases (if credentials provided), and download your fine-tuned model once the job is completed.

Understanding the cost associated with fine-tuning jobs is crucial. This page provides detailed information on our billing process, including how jobs are billed, the cost per minute, and what happens if your account runs out of credits. Furthermore, it provides guidance on how to maintain an active payment method and subscription plan to avoid job termination.

Visit each page to get detailed information on each process. If you have any questions or need further assistance, feel free to reach out to our support team.

For any queries, don't hesitate to reach us out at MonsterAPI Support.

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