skills.rest
DMT123
DMT123COMMUNITY
Explore all skills by this author →
GitHub

hugging-face-jobs

Execute Python scripts or Docker images on managed Hugging Face cloud infrastructure.

Updated Mar 2, 2026
Search Tags:#model training#data processing#hugging face#cloud compute#gpu jobs#batch inference
One-click install
npx skills add https://github.com/DMT123/claude-skills-collection --skill hugging-face-jobs-dmt123
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: hugging-face-jobs
Source: https://github.com/DMT123/claude-skills-collection/tree/main/plugins/huggingface/hugging-face-jobs
Command: npx skills add https://github.com/DMT123/claude-skills-collection --skill hugging-face-jobs-dmt123

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires huggingface-hub, datasets, transformers, vllm, torch, polars, flashinfer-python, hf-xet, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the execution of complex computational tasks, such as data processing, model training, and batch inference, on scalable cloud infrastructure without requiring local setup.

Core Features & Use Cases

  • Cloud Compute: Run Python scripts or Docker containers on managed CPU, GPU, or TPU instances.
  • Authentication: Securely handles Hugging Face tokens for Hub interactions.
  • Persistence: Ensures results are saved by pushing them to the Hugging Face Hub.
  • Scheduling: Automates recurring tasks with cron-like scheduling.
  • Use Case: Train a large language model on a GPU cluster, process terabytes of data, or run batch inference for thousands of samples, all managed through a simple interface.

Quick Start

Use the hugging-face-jobs skill to run a Python script named 'train_model.py' on a GPU instance.

Frequently Asked Questions about hugging-face-jobs

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

FAQPage Schema
How do I run model training on cloud compute infrastructure without local setup?▼

Run batch inference on Hugging Face Jobs by submitting Python scripts with PEP 723 dependencies or custom Docker images. This Skill manages authentication and executes workloads on managed CPU, GPU, or TPU instances.

Can I use custom Docker images for batch inference on Hugging Face?▼

Yes, you can use custom Docker images for batch inference on Hugging Face. This Skill supports executing arbitrary Docker containers on managed cloud instances, handling authentication and hardware selection automatically.

Does Hugging Face Jobs support scheduling recurring data processing tasks?▼

Hugging Face Jobs supports scheduling recurring data processing tasks via cron-like automation. You can automate scalable data processing workloads and persist the resulting outputs directly to the Hugging Face Hub.

What dependencies are required to process terabytes of data using Hugging Face Jobs?▼

Processing terabytes of data using Hugging Face Jobs requires dependencies like datasets, polars, and huggingface-hub. The Skill executes Python scripts on scalable cloud infrastructure and manages result persistence to the Hub.

Are there limitations when running large language model training on managed cloud instances?▼

Limitations when running large language model training on managed cloud instances include hardware selection constraints and configured timeouts. You must ensure results are explicitly pushed to the Hugging Face Hub for persistence.

Related Skills

Explore More Software Engineering Skills→
FacuMFacuM

hugging-face-jobs

Execute Python scripts and Docker images on Hugging Face cloud infrastructure.

Community
Advanced
mashharukimashharuki

hugging-face-jobs

Run Python workloads on managed Hugging Face Jobs infrastructure.

Community
Advanced
heysuhasheysuhas
2

modal-serverless-gpu

Deploy Python functions as auto-scaling serverless GPU endpoints.

Community
Advanced
keremtoker468-dotcomkeremtoker468-dotcom

hf-jobs

Execute Python scripts or Docker images on Hugging Face cloud infrastructure.

Community
Advanced