---
name: Hugging Face Cli
description: Execute Hugging Face Hub operations using the `hf` CLI. Use when the user needs to download models/datasets/spaces, upload files to Hub repositories, create repos, manage local cache, or run comput...
---

# Hugging Face Cli

Execute Hugging Face Hub operations using the `hf` CLI. Use when the user needs to download models/datasets/spaces, upload files to Hub repositories, create repos, manage local cache, or run compute jobs on HF infrastructure. Covers authentication, file transfers, repository creation, cache operations, and cloud compute.

# Hugging Face Cliby huggingface
Execute Hugging Face Hub operations using the `hf` CLI. Use when the user needs to download models/datasets/spaces, upload files to Hub repositories, create repos, manage local cache, or run compute jobs on HF infrastructure. Covers authentication, file transfers, repository creation, cache operations, and cloud compute.

`npx skills add https://github.com/huggingface/skills --skill hugging-face-cli`Download ZIPGitHub

## More skills from huggingface
Hugging Face Datasetsby huggingfaceCreate and manage datasets on Hugging Face Hub. Supports initializing repos, defining configs/system prompts, streaming row updates, and SQL-based dataset querying/transformation. Designed to work alongside HF MCP server for comprehensive dataset workflows.Hugging Face Evaluationby huggingfaceAdd and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom model evaluations with vLLM/lighteval. Works with the model-index metadata format.Hugging Face Jobsby huggingfaceRun any workload on Hugging Face Jobs infrastructure. Covers UV scripts, Docker-based jobs, hardware selection, cost estimation, authentication with tokens, secrets management, timeout configuration, and result persistence. Designed for general-purpose compute workloads including data processing, inference, experiments, batch jobs, and any Python-based tasks.Hugging Face Model Trainerby huggingfaceTrain or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on dataset preparation, hardware selection, cost estimation, and model persistence.Hugging Face Paper Publisherby huggingfacePublish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.Hugging Face Tool Builderby huggingfaceBuild reusable scripts and tools using the Hugging Face API. Useful when chaining or combining API calls, or when tasks will be repeated/automated. Creates reusable command line scripts to fetch, enrich, or process data from Hugging Face Hub.Hugging Face Trackioby huggingfaceTrack and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API) or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, HF Space syncing, and JSON output for automation.add-model-descriptionsby huggingfaceAdd descriptions for new models from the HuggingFace router to chat-ui configuration. Use when new models are released on the router and need descriptions…

---

**Source**: https://github.com/huggingface/skills/tree/main/skills/hugging-face-cli
**Author**: huggingface
**Discovered via**: mcpservers.org