Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly

Appearance settings
This repository was archived by the owner on Aug 12, 2025. It is now read-only.

ryhkml/fine-tune-forge

Open more actions menu

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

45 Commits
45 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

FineTuneForge

FineTuneForge is a tool designed specifically for generating JSON Lines (JSONL) to facilitate the fine-tuning of AI language models like Google's PaLM 2 and OpenAI's GPT-3.5. It enables developers to easily transform text data into a JSONL format that machines can read.

Screenshot FineTuneForge Webapp

Getting Started

Warning

DO NOT USE IN PRODUCTION

This project has no CSRF protection. I'm unsure if i will implement it. For example, i created a new CSRF protection in Angular SSR 18. See it here

To get started with FineTuneForge, follow these steps:

Installation

git clone https://github.com/ryhkml/fine-tune-forge.git
cd fine-tune-forge
./install.sh

Usage

Run the JSONL generator with the following command:

npm run build

Serve server

npm run serve

Or using docker/podman compose

docker compose -p ftf --env-file .env up -d --build

Update

After performing a git pull, just run the following command:

./update.sh

Directory Structure

FineTuneForge is organized into several directories, each serving a specific purpose in the workflow of the JSONL generator. Below is an overview of these directories and their intended use:

  • DATADOC_OCR: This directory acts as a temporary storage for OCR (Optical Character Recognition) images
  • DATASET: The DATASET directory is the designated location for storing the completed dataset files. Once the JSONL files have been generated and are ready for use in fine-tuning the language models, they are placed in this directory
  • DATATMP: This directory for temporary storage of instruction content
  • tls: This directory is reserved for storing SSL/TLS certificates

Configuring SSL/TLS for HTTPS

To enable HTTPS in the application, you need to configure SSL/TLS certificates correctly.

Required Files

Before you start, ensure you have the following files placed in the tls directory:

  • fullchain.pem: This is your certificate file that contains the full chain of trust, including any intermediate certificates along with your own
  • cert-key.pem: This file contains your private key and must be kept secure. It is used to establish the encrypted connection
  • ca.crt (optional): This Certificate Authority (CA) file is used if you need to specify an external CA

If you use docker, uncomment the environment variable PROTOCOL_SERVER in docker-compose.yaml

License

This project is licensed under the MIT License - see the LICENSE file for details.

About

JSONL generator designed for models like Google PaLM 2 and OpenAI GPT-3.5

Topics

Resources

Stars

Watchers

Forks

Releases

Used by

Contributors

Languages

Morty Proxy This is a proxified and sanitized view of the page, visit original site.