MY FRIEND IS STILL PAYING FOR GMAIL STORAGE.
I told him to do this before.
He went from 14.9/15 GB to 6 GB in a single afternoon.
Hope this helps you ↓
Fine-tuning an LLM used to require a PhD. Now it takes 3 clicks.
We have been gatekept by complex Python scripts and "CUDA OOM" errors for too long.
I found the tool that democratizes custom models. It’s called LlamaFactory.
It is the "Automatic1111" for Large Language Models.
The "Cheat Code" => It provides a WebUI (LlamaBoard) that lets you visually configure, train, and evaluate models without writing a single line of code.
This unlocks "Zero-Code" Fine-Tuning for everyone:
1./ Day-0 Model Support
It supports 100+ Models out of the box. Llama 3 (and 4!), Mistral, Qwen, Gemma, DeepSeek, Phi-3... if it's on Hugging Face, it's likely here.
2./ Advanced Techniques Made Simple
Want to run QLoRA (4-bit tuning) on a consumer GPU? Want to align your model with DPO or ORPO? It’s just a dropdown menu. No complex math required. It even integrates Unsloth for 2x faster training.
3./ Visual Monitoring
Stop staring at terminal logs. Watch your loss curves and evaluate model outputs in real-time directly inside the browser (LlamaBoard).
It runs locally, on Colab, or on your server.
Stop writing training loops. Start building models.