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openclaw-huggingfaceOpenClaw huggingface 搜索

Agent Skill

openclaw-huggingface 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

14,762

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609

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下载量

4,823
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:openclaw-huggingface(OpenClaw huggingface 搜索)
来源仓库:https://github.com/tsukisama9292/openclaw-huggingface
安装命令:
openclaw skills install openclaw-huggingface
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install openclaw-huggingface

简介

使用 Hugging Face CLI (hf) 管理模型、数据集、空间和存储库。支持认证、上传、下载、创建空间等。

SKILL.md

name
openclaw-huggingface
description
Manage models, datasets, Spaces, and repositories using Hugging Face CLI (hf). Supports authentication, upload, download, Space creation, and more.
metadata
{"openclaw":{"emoji":"🤗","requires":{"bins":["hf"],"env":["HF_TOKEN"]}}}

Hugging Face CLI Skill

Use Hugging Face Hub CLI (hf) for various operations.

Environment Variables

  • HF_TOKEN: Hugging Face API Token (get from https://huggingface.co/settings/tokens)

Core Features

1. Authentication Management (hf auth)

# Check login status
hf auth whoami

# List all tokens
hf auth list

# Login
hf auth login

# Logout
hf auth logout

# Switch token
hf auth switch

2. Model Management (hf models)

# List models (supports sorting and filtering)
hf models ls --sort downloads --limit 10
hf models ls --search "llama"

# Get model info
hf models info meta-llama/Llama-3.2-1B-Instruct

3. Dataset Management (hf datasets)

# List datasets
hf datasets ls --limit 10
hf datasets ls --search "imagenet"

# Get dataset info
hf datasets info HuggingFaceFW/fineweb

4. Spaces Management (hf spaces)

# List Spaces
hf spaces ls --limit 10

# Get Space info
hf spaces info username/repo-name

# Hot-reload (experimental, for Gradio 6.1+)
hf spaces hot-reload username/repo-name app.py
hf spaces hot-reload username/repo-name -f ./local/app.py

5. Repository Management (hf repos)

# Create new repository
hf repos create my-model --type model
hf repos create my-dataset --type dataset
hf repos create my-space --type space

# Delete repository
hf repos delete username/repo-name

# Set as private
hf repos settings username/repo-name --private

# Manage branches
hf repos branch create username/repo-name feature-branch
hf repos branch delete username/repo-name feature-branch

# Manage tags
hf repos tag create username/repo-name v1.0
hf repos tag delete username/repo-name v1.0

# Move repository to another namespace
hf repos move old-namespace/my-model new-namespace/my-model

6. Download Files (hf download)

# Download entire model
hf download meta-llama/Llama-3.2-1B-Instruct

# Download specific files
hf download meta-llama/Llama-3.2-1B-Instruct config.json tokenizer.json

# Download with glob patterns
hf download meta-llama/Llama-3.2-1B-Instruct --include "*.safetensors"
hf download meta-llama/Llama-3.2-1B-Instruct --include "*.json" --exclude "*.bin"

# Download to local directory
hf download meta-llama/Llama-3.2-1B-Instruct --local-dir ./models/llama

# Download dataset
hf download HuggingFaceM4/FineVision --repo-type dataset

7. Upload Files (hf upload)

# Upload entire directory
hf upload my-cool-model . .

# Upload single file
hf upload username/my-model ./models/model.safetensors

# Upload to dataset
hf upload username/my-dataset ./data /train --repo-type dataset

# With commit message
hf upload username/my-model ./models . --commit-message="Epoch 34/50" --commit-description="Val accuracy: 68%"

# Create Pull Request
hf upload bigcode/the-stack . . --repo-type dataset --create-pr

# Create private repository
hf upload username/my-private-model . . --private

8. Collection Management (hf collections)

# Create collection
hf collections create "My Models"

# Add item to collection
hf collections add-item username/my-collection moonshotai/kimi-k2 model

# List collections
hf collections ls

# Get collection info
hf collections info username/my-collection

# Update collection
hf collections update username/my-collection --title "New Title"

# Update collection item
hf collections update-item username/my-collection ITEM_OBJECT_ID --note "Updated note"

# Delete item
hf collections delete-item username/my-collection ITEM_OBJECT_ID

# Delete collection
hf collections delete username/my-collection

Usage Examples

Example 1: Download and Upload Model

# Download model
hf download meta-llama/Llama-3.2-1B-Instruct --local-dir ./llama-model

# Upload to your repository
hf upload username/my-llama ./llama-model .

Example 2: Manage Space

# Create Space
hf repos create my-app --type space

# Upload code
hf upload username/my-app ./app.py

# Hot-reload for development
hf spaces hot-reload username/my-app app.py

Example 3: Batch Operations

# Download all safetensors files
hf download meta-llama/Llama-3.2-1B-Instruct --include "*.safetensors"

# Upload and create PR
hf upload username/model . . --create-pr --commit-message="Update model"

Notes

  1. Token Management: Ensure HF_TOKEN environment variable is set, or use --token parameter
  2. Large File Upload: For large folders, consider using hf upload-large-folder
  3. Space Hot-Reload: Only works with Gradio 6.1+, experimental feature
  4. Free Space Limits:

- Free fixed vCPU: 2 - RAM: 16GB - No persistent storage (use external storage or HF Datasets)

Resources

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

73.09%
按下载量换算3,525

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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