Train AI models with Unsloth and Hugging Face Jobs for ...

Train AI models with Unsloth and Hugging Face Jobs for FREE Back to Articles Train AI models with Unsloth and Hugging Face Jobs for FREE Published February 20, 2026 Upvote 103 - +97 ben burtenshaw burtenshaw Follow Daniel (Unsloth) danielhanchen Follow unsloth Michael Han shimmyshimmer Follow unsloth Maxime Labonne mlabonne Follow LiquidAI Daniel van Strien davanstrien Follow shaun smith evalstate Follow This blog post covers how to use Unsloth and Hugging Face Jobs for fast LLM fine-tuning (specifically LiquidAI/LFM2.5-1.2B-Instruct) through coding agents like Claude Code and Codex. Unsloth provides ~2x faster training and ~60% less VRAM usage compared to standard methods, so training small models can cost just a few dollars. Why a small model? Small language models like LFM2.5-1.2B-Instruct are ideal candidates for fine-tuning. They are cheap to train, fast to iterate on, and increasingly competitive with much larger models on focused tasks. LFM2.5-1.2B-Instruct runs under 1GB of memory and is optimized for on-device deployment, so what you fine-tune can be served on CPUs, phones, and laptops. You will need We are giving away free credits to fine-tune models on Hugging Face Jobs. Join the Unsloth Jobs Explorers organization to claim your free credits and one-month Pro subscription. - A Hugging Face account (required for HF Jobs) - Billing setup (for verification, you can monitor your usage and manage your billing in your billing page). - A Hugging Face token with write permissions - (optional) A coding agent (`Open Code`,`Claude Code`, or`Codex`) Run the Job If you want to train a model using HF Jobs and Unsloth, you can simply use the`hf jobs` CLI to submit a job. First, you need to install the`hf` CLI. You can do this by running the following command: ``` mac or linux curl -LsSf https://hf.co/cli/install.sh | bash ``` Next you can run the following command to submit a job: ``` hf jobs uv run https://huggingface.co/datasets/uns