huggingface-hub

---
name: huggingface-hub
description: Hugging Face Hub CLI (hf) — search, download, and upload models and datasets, manage repos, query datasets with SQL, deploy inference endpoints, manage Spaces and buckets.
version: 1.0.0
author: Hugging Face
license: MIT
tags: [huggingface, hf, models, datasets, hub, mlops]
---

# Hugging Face CLI (`hf`) Reference Guide

The `hf` command is the modern command-line interface for interacting with the Hugging Face Hub, providing tools to manage repositories, models, datasets, and Spaces.

> **IMPORTANT:** The `hf` command replaces the now deprecated `huggingface-cli` command.

## Quick Start
*   **Installation:** `curl -LsSf https://hf.co/cli/install.sh | bash -s`
*   **Help:** Use `hf --help` to view all available functions and real-world examples.
*   **Authentication:** Recommended via `HF_TOKEN` environment variable or the `--token` flag.

---

## Core Commands

### General Operations
*   `hf download REPO_ID`: Download files from the Hub.
*   `hf upload REPO_ID`: Upload files/folders (recommended for single-commit).
*   `hf upload-large-folder REPO_ID LOCAL_PATH`: Recommended for resumable uploads of large directories.
*   `hf sync`: Sync files between a local directory and a bucket.
*   `hf env` / `hf version`: View environment and version details.

### Authentication (`hf auth`)
*   `login` / `logout`: Manage sessions using tokens from [huggingface.co/settings/tokens](https://huggingface.co/settings/tokens).
*   `list` / `switch`: Manage and toggle between multiple stored access tokens.
*   `whoami`: Identify the currently logged-in account.

### Repository Management (`hf repos`)
*   `create` / `delete`: Create or permanently remove repositories.
*   `duplicate`: Clone a model, dataset, or Space to a new ID.
*   `move`: Transfer a repository between namespaces.
*   `branch` / `tag`: Manage Git-like references.
*   `delete-files`: Remove specific files using patterns.

---

## Specialized Hub Interactions

### Datasets & Models
*   **Datasets:** `hf datasets list`, `info`, and `parquet` (list parquet URLs).
*   **SQL Queries:** `hf datasets sql SQL` — Execute raw SQL via DuckDB against dataset parquet URLs.
*   **Models:** `hf models list` and `info`.
*   **Papers:** `hf papers list` — View daily papers.

### Discussions & Pull Requests (`hf discussions`)
*   Manage the lifecycle of Hub contributions: `list`, `create`, `info`, `comment`, `close`, `reopen`, and `rename`.
*   `diff`: View changes in a PR.
*   `merge`: Finalize pull requests.

### Infrastructure & Compute
*   **Endpoints:** Deploy and manage Inference Endpoints (`deploy`, `pause`, `resume`, `scale-to-zero`, `catalog`).
*   **Jobs:** Run compute tasks on HF infrastructure. Includes `hf jobs uv` for running Python scripts with inline dependencies and `stats` for resource monitoring.
*   **Spaces:** Manage interactive apps. Includes `dev-mode` and `hot-reload` for Python files without full restarts.

### Storage & Automation
*   **Buckets:** Full S3-like bucket management (`create`, `cp`, `mv`, `rm`, `sync`).
*   **Cache:** Manage local storage with `list`, `prune` (remove detached revisions), and `verify` (checksum checks).
*   **Webhooks:** Automate workflows by managing Hub webhooks (`create`, `watch`, `enable`/`disable`).
*   **Collections:** Organize Hub items into collections (`add-item`, `update`, `list`).

---

## Advanced Usage & Tips

### Global Flags
*   `--format json`: Produces machine-readable output for automation.
*   `-q` / `--quiet`: Limits output to IDs only.

### Extensions & Skills
*   **Extensions:** Extend CLI functionality via GitHub repositories using `hf extensions install REPO_ID`.
*   **Skills:** Manage AI assistant skills with `hf skills add`.

## Activation Keywords

- "huggingface-hub"
- "huggingface hub"
- "use huggingface hub"
- "huggingface hub help"
- "huggingface hub tool"

## Tools Used

- `Read` - Read existing files and documentation
- `Write` - Create new files and documentation
- `Bash` - Execute commands when needed

## Instructions for Agents

1. Identify user's intent and specific requirements
2. Gather necessary context from files or user input
3. Execute appropriate actions using available tools
4. Provide clear results and suggest next steps

## Examples

### Basic Huggingface Hub usage
```
User: "Help me with huggingface hub"
→ Understand requirements → Execute actions → Provide results
```

### Advanced usage
```
User: "I need detailed huggingface hub assistance"
→ Clarify scope → Provide comprehensive solution → Follow up
```