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unsloth-hf-jobs

Fine-tune LLMs and VLMs on HF Jobs with Unsloth for GPU training.

8|Updated Jan 9, 2026
Search Tags:#llm#lora#finetuning#hf-jobs#unsloth#vlm#gpu-training
One-click install
npx skills add https://github.com/svngoku/coding-agents-skills --skill unsloth-hf-jobs
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: unsloth-hf-jobs
Source: https://github.com/svngoku/coding-agents-skills/tree/main/skills/unsloth-hf-jobs
Command: npx skills add https://github.com/svngoku/coding-agents-skills --skill unsloth-hf-jobs

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires unsloth, datasets, trl, huggingface_hub[hf_transfer], trackio, transformers==4.56.2, transformers==4.57.1, trl==0.22.2, tensorboard, and includes scripts (resource) components.

What problem does it solve?

Fine-tune LLMs and VLMs on HF Jobs using Unsloth to accelerate GPU-based training and deployment.

Core Features & Use Cases

  • Efficient fine-tuning of LLMs and VLMs using Unsloth on HF Jobs for scalable GPU training.
  • Supports domain adaptation, continued pretraining, and LoRA-style fine-tuning on cloud GPUs.
  • Use Case: Quickly adapt a base model to a new domain and push adapters to HuggingFace Hub for sharing.

Quick Start

Launch a quick HF Jobs run to fine-tune your model with Unsloth and push the resulting adapter to HuggingFace Hub.

Frequently Asked Questions about unsloth-hf-jobs

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I fine-tune LLMs and VLMs with Unsloth on cloud GPUs?▼

You can fine-tune LLMs and VLMs on cloud GPUs by running Unsloth on HF Jobs. This setup accelerates GPU-based training and supports pushing the resulting adapters directly to the HuggingFace Hub.

Can I use LoRA-style fine-tuning and 4-bit training for domain adaptation on HF Jobs?▼

Yes, HF Jobs supports LoRA-style fine-tuning and 4-bit training using Unsloth. This allows efficient domain adaptation and continued pretraining for both language and vision-language models on scalable cloud GPUs.

What dependencies do I need to run Unsloth for GPU training on HuggingFace Jobs?▼

You need dependencies including unsloth, datasets, trl, huggingface_hub with hf_transfer, trackio, and transformers. Tensorboard is also included to support tooling and monitoring during GPU training.

Does Unsloth on HF Jobs support pushing trained adapters to the HuggingFace Hub?▼

Yes, after you fine-tune your model with Unsloth on HF Jobs, you can quickly adapt a base model to a new domain and push the resulting adapters to HuggingFace Hub for sharing.

How do I track GPU training metrics when fine-tuning models with Unsloth?▼

You can track GPU training metrics using the included trackio and tensorboard dependencies. These tools provide monitoring and tooling support during the Unsloth fine-tuning process on HF Jobs.

What is the best way to accelerate continued pretraining for vision-language models?▼

Using Unsloth on HF Jobs is an efficient way to accelerate continued pretraining for vision-language models. It enables scalable GPU training and supports 4-bit quantization to optimize resource usage.

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