hugging-face-cli

Hugging Face CLI

hf CLI 可直接在终端访问 Hugging Face Hub，用于下载、上传和管理仓库、缓存及计算资源。

快速命令参考

任务	命令
登录	hf auth login
下载模型	hf download <repo_id>
下载到文件夹	hf download <repo_id> --local-dir ./path
上传文件夹	hf upload <repo_id> . .
创建仓库	hf repo create <name>
创建标签	hf repo tag create <repo_id> <tag>
删除文件	hf repo-files delete <repo_id> <files>
列出缓存	hf cache ls
从缓存中移除	hf cache rm <repo_or_revision>
列出模型	hf models ls
获取模型信息	hf models info <model_id>
列出数据集	hf datasets ls
获取数据集信息	hf datasets info <dataset_id>
列出 Spaces	hf spaces ls
获取 Space 信息	hf spaces info <space_id>
列出端点	hf endpoints ls
运行 GPU 作业	hf jobs run --flavor a10g-small <image> <cmd>
环境信息	hf env

核心命令

身份验证

hf auth login                    # Interactive login
hf auth login --token $HF_TOKEN  # Non-interactive
hf auth whoami                   # Check current user
hf auth list                     # List stored tokens
hf auth switch                   # Switch between tokens
hf auth logout                   # Log out

下载

hf download <repo_id>                              # Full repo to cache
hf download <repo_id> file.safetensors             # Specific file
hf download <repo_id> --local-dir ./models         # To local directory
hf download <repo_id> --include "*.safetensors"    # Filter by pattern
hf download <repo_id> --repo-type dataset          # Dataset
hf download <repo_id> --revision v1.0              # Specific version

上传

hf upload <repo_id> . .                            # Current dir to root
hf upload <repo_id> ./models /weights              # Folder to path
hf upload <repo_id> model.safetensors              # Single file
hf upload <repo_id> . . --repo-type dataset        # Dataset
hf upload <repo_id> . . --create-pr                # Create PR
hf upload <repo_id> . . --commit-message="msg"     # Custom message

仓库管理

hf repo create <name>                              # Create model repo
hf repo create <name> --repo-type dataset          # Create dataset
hf repo create <name> --private                    # Private repo
hf repo create <name> --repo-type space --space_sdk gradio  # Gradio space
hf repo delete <repo_id>                           # Delete repo
hf repo move <from_id> <to_id>                     # Move repo to new namespace
hf repo settings <repo_id> --private true          # Update repo settings
hf repo list --repo-type model                     # List repos
hf repo branch create <repo_id> release-v1         # Create branch
hf repo branch delete <repo_id> release-v1         # Delete branch
hf repo tag create <repo_id> v1.0                  # Create tag
hf repo tag list <repo_id>                         # List tags
hf repo tag delete <repo_id> v1.0                  # Delete tag

删除仓库文件

hf repo-files delete <repo_id> folder/             # Delete folder
hf repo-files delete <repo_id> "*.txt"             # Delete with pattern

缓存管理

hf cache ls                      # List cached repos
hf cache ls --revisions          # Include individual revisions
hf cache rm model/gpt2           # Remove cached repo
hf cache rm <revision_hash>      # Remove cached revision
hf cache prune                   # Remove detached revisions
hf cache verify gpt2             # Verify checksums from cache

浏览 Hub

# Models
hf models ls                                        # List top trending models
hf models ls --search "MiniMax" --author MiniMaxAI  # Search models
hf models ls --filter "text-generation" --limit 20  # Filter by task
hf models info MiniMaxAI/MiniMax-M2.1               # Get model info

# Datasets
hf datasets ls                                      # List top trending datasets
hf datasets ls --search "finepdfs" --sort downloads # Search datasets
hf datasets info HuggingFaceFW/finepdfs             # Get dataset info

# Spaces
hf spaces ls                                        # List top trending spaces
hf spaces ls --filter "3d" --limit 10               # Filter by 3D modeling spaces
hf spaces info enzostvs/deepsite                    # Get space info

作业（云计算）

hf jobs run python:3.12 python script.py           # Run on CPU
hf jobs run --flavor a10g-small <image> <cmd>      # Run on GPU
hf jobs run --secrets HF_TOKEN <image> <cmd>       # With HF token
hf jobs ps                                         # List jobs
hf jobs logs <job_id>                              # View logs
hf jobs cancel <job_id>                            # Cancel job

推理端点

hf endpoints ls                                     # List endpoints
hf endpoints deploy my-endpoint \
  --repo openai/gpt-oss-120b \
  --framework vllm \
  --accelerator gpu \
  --instance-size x4 \
  --instance-type nvidia-a10g \
  --region us-east-1 \
  --vendor aws
hf endpoints describe my-endpoint                   # Show endpoint details
hf endpoints pause my-endpoint                      # Pause endpoint
hf endpoints resume my-endpoint                     # Resume endpoint
hf endpoints scale-to-zero my-endpoint              # Scale to zero
hf endpoints delete my-endpoint --yes               # Delete endpoint

GPU 规格： cpu-basic、cpu-upgrade、cpu-xl、t4-small、t4-medium、l4x1、l4x4、l40sx1、l40sx4、l40sx8、a10g-small、a10g-large、a10g-largex2、a10g-largex4、a100-large、h100、h100x8

常见用法

在本地下载并使用模型

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

# Or use cache and get path
MODEL_PATH=$(hf download meta-llama/Llama-3.2-1B-Instruct --quiet)

发布模型/数据集

hf repo create my-username/my-model --private
hf upload my-username/my-model ./output . --commit-message="Initial release"
hf repo tag create my-username/my-model v1.0

将 Space 与本地同步

hf upload my-username/my-space . . --repo-type space \
  --exclude="logs/*" --delete="*" --commit-message="Sync"

检查缓存使用情况

hf cache ls                      # See all cached repos and sizes
hf cache rm model/gpt2           # Remove a repo from cache

关键选项

• --repo-type：model（默认）、dataset、space
• --revision：分支、标签或提交哈希
• --token：覆盖身份验证
• --quiet：仅输出必要信息（路径/URL）

参考资料

• 完整命令参考：参见 references/commands.md
• 工作流示例：参见 references/examples.md