Unsloth Studio
Local, browser-based GUI for fine-tuning LLMs without writing code. Supports QLoRA, LoRA, and full fine-tuning with live training monitoring, GPU stats, and model export to GGUF/Safetensors.
Install
bash -c "$(curl -fsSL https://raw.githubusercontent.com/Heretek-AI/ProxmoxVE/main/ct/unsloth-studio.sh)"Run as root in the Proxmox VE shell. Pick Default for the sizing below, or Advanced to choose storage, network and resources yourself.
Notes
- Warning: Default credentials: username 'unsloth', password is randomly generated and shown in logs. Run 'journalctl -u unsloth-studio | grep password' to find it.
- Warning: First launch takes 5-10 minutes to compile llama.cpp binaries.
- Warning: ROCm support for Unsloth Studio is not yet implemented. See https://github.com/unslothai/unsloth/pull/4390 for progress.
- Requires GPU passthrough for training. NVIDIA, AMD (ROCm), and Intel GPUs are supported.
- Minimum 16GB RAM recommended for training models up to 7B parameters.
- For AMD GPUs, ensure ROCm is properly configured on the host.
Script details
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