| title | LLM Fine-Tuner v3.2 | ||||||||||
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| emoji | 🧠 | ||||||||||
| colorFrom | indigo | ||||||||||
| colorTo | purple | ||||||||||
| sdk | gradio | ||||||||||
| sdk_version | 5.0.0 | ||||||||||
| python_version | 3.10 | ||||||||||
| app_file | app.py | ||||||||||
| pinned | false | ||||||||||
| suggested_hardware | l4x1 | ||||||||||
| suggested_storage | large | ||||||||||
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Your own custom AI — no coding, no PhD, no drama.
Upload your data → click Train → get a ready-to-use model in minutes.
Imagine you could take a smart AI assistant and teach it to be an expert in your specific topic — your business, your writing style, your data. That's exactly what fine-tuning is.
LLM Fine-Tuner lets you do it through a simple visual interface. No programming knowledge needed. If you can use a spreadsheet and a web browser, you can fine-tune an AI model.
What you can build:
- 💼 A customer support bot that knows your products inside and out
- ✍️ A writing assistant that matches your exact tone and style
- 🏥 A domain expert trained on your specialised knowledge
- 🎮 A character AI with a specific personality
- 📚 A Q&A tool trained on your own documents
- No coding — Everything happens through a point-and-click interface
- Works on regular hardware — Even a gaming laptop with 8 GB of GPU memory is enough
- Fast — Train a model in minutes, not days
- Your data stays yours — Everything runs on your own machine
- Export anywhere — Use your model in Ollama, LM Studio, or share it online
Think of fine-tuning like a master craftsman shaping raw material into a precision tool. The AI already knows a lot — you're just focusing that knowledge toward exactly what you need.
LLM Fine-Tuner uses Unsloth under the hood — a turbo engine that makes training 2–5× faster and uses dramatically less memory. Even a regular gaming GPU becomes a fine-tuning powerhouse.
Some AI models have built-in restrictions that get in the way. Heretic Mode lets you remove those restrictions with one click. Use it responsibly — with great power comes great responsibility.
# Download the project
git clone https://github.com/Yog-Sotho/LLM-fine-tuner.git
cd LLM-fine-tuner
# Run the installer — it handles everything for you
chmod +x install.sh && ./install.shThe installer will ask you a few yes/no questions. When it's done, launch with:
source llm_finetuner_env/bin/activate
llm-finetuneYour browser opens automatically. You're ready to train.
./install.sh --yespip install -r requirements.txt
python main.pyUsing Google Colab? You can run this entirely in your browser with a free GPU. See the full installation guide.
Create a simple spreadsheet (CSV file) with two columns:
| instruction | output |
|---|---|
| What are your opening hours? | We're open Monday to Saturday, 9am to 6pm. |
| Do you offer refunds? | Yes! We offer full refunds within 30 days of purchase. |
| Where are you located? | We're at 123 Main Street, downtown. |
That's it. No special formatting, no coding. Just questions and the answers you want the model to give.
Don't have a CSV? The tool also accepts Word docs, PDFs, Excel files, plain text files, and more.
- Open the app (it runs in your browser)
- Click 📂 Data and upload your file
- Click 🚀 Training, pick a preset, and hit ▶ Start Training
- Watch the progress bar — training takes minutes to an hour depending on your hardware
- Go to 💬 Inference and type a question
- Your model responds using everything it learned from your data
- When happy, go to 📤 Share to download or publish your model
| Format | How to create it |
|---|---|
| CSV | Save any spreadsheet as CSV from Excel or Google Sheets |
| Excel (.xlsx) | Drag in your Excel file directly |
| JSON / JSONL | Export from your database or app |
| Plain text (.txt) | One example per line |
| Any PDF document — text is extracted automatically | |
| ZIP | Put multiple files in a ZIP and upload them all at once |
You don't need to understand all of these to get started — the defaults work great. But here's what they mean if you're curious:
| Option | What it does | Beginner recommendation |
|---|---|---|
| Training Preset | Quick = fast test, Balanced = good results, Accurate = best quality | Start with Balanced |
| Base Model | The starting AI brain you're teaching | Leave on Auto — the tool picks the right one for your hardware |
| PEFT Method | How the training is done internally | Leave on Auto |
| Unsloth | Turbo mode — makes training much faster | Always turn ON if available |
| Heretic Mode | Removes built-in restrictions from the model | Optional — use responsibly |
| Mode | What it does | When to use it |
|---|---|---|
| Standard Training (SFT) | Teaches the model using your question-answer examples | Starting point for almost everyone |
| Preference Training (DPO) | Teaches the model which answers are better vs worse | After standard training, to improve quality |
| Reward + PPO | Advanced alignment with a scoring system | When you want the highest quality alignment |
| ORPO | Modern single-step alignment | Faster alternative to full Reward + PPO |
Once trained, your model can be:
- Downloaded as a ZIP — keep a backup on your computer
- Published to HuggingFace Hub — share it with the world (or keep it private)
- Exported as GGUF — run it offline with Ollama or LM Studio on any computer, even without internet
- Served with vLLM — high-speed serving for multiple users at once
Already available in v3.2:
- ✅ Visual interface — no coding needed
- ✅ All major training modes (SFT, DPO, RLHF, ORPO)
- ✅ GGUF export for Ollama & LM Studio
- ✅ Heretic Mode
- ✅ Command-line mode for power users
- ✅ Batch evaluation tools
- ✅ Data augmentation
Coming soon:
- 🔲 Synthetic data generator — create training data with AI
- 🔲 Docker image — one-command setup with no dependencies
- 🔲 Multi-GPU training
- 🔲 Vision + language models
New to fine-tuning? The docs are written for non-technical users:
| Guide | What you'll learn |
|---|---|
| Installation | 4 ways to install, including Google Colab |
| Quick Start | Train your first model in 5 minutes |
| Preparing Your Data | How to format your CSV, fix column names |
| Training Guide | All settings explained in plain English |
| Exporting Your Model | Download, publish, or deploy |
| Troubleshooting | Fix the most common errors |
| FAQ | Quick answers to common questions |
Contributions welcome! Fork the repo, make your changes, and open a pull request with a clear description of what you did and why.
Found a bug? Open an issue with your OS, GPU model, and the full error message.
GPL-3.0 — free to use, modify, and share. Attribution appreciated ❤️
Made with ❤️ for the open-source community
If this tool helped you build something cool, a ⭐ on GitHub means the world. Yog-Sotho