Linux command
hf 命令
文本
复制后可按需替换文件名、目录或参数。
常用示例
Log in to Hugging Face
hf auth login
Download a model
hf download [gpt2]
Download specific files
hf download [meta-llama/Llama-2-7b] [config.json] [model.safetensors]
Upload a folder
hf upload [username/my-model] [./models] [.]
List trending models
hf models ls
Run a job on GPU
hf jobs run --flavor [a10g-small] [pytorch/pytorch:2.6.0-cuda12.4-cudnn9-devel] [python train.py]
View cache usage
hf cache ls
说明
hf (formerly huggingface-cli) is the official command-line interface for Hugging Face Hub. It provides direct terminal access to download models and datasets, upload files, manage repositories, run compute jobs, and interact with the ML community platform. The CLI follows a consistent hf resource action pattern. Files are cached locally in ~/.cache/huggingface/hub/ with smart deduplication. The download command supports partial downloads with --include/--exclude patterns and resumable transfers. hf jobs enables running code on Hugging Face infrastructure including GPUs (T4, A10G, A100) and TPUs, with Docker-like commands. Jobs support environment variables, secrets, scheduled execution, and UV scripts for self-contained Python tasks. Authentication is managed via hf auth login which stores tokens locally. Tokens can also be set via the HF_TOKEN environment variable for scripting.
参数
- --repo-type _type_
- Repository type: model, dataset, or space.
- --revision _ref_
- Specific revision (branch, tag, or commit hash).
- --local-dir _path_
- Download to specific local directory instead of cache.
- --include _pattern_
- Include files matching glob pattern.
- --exclude _pattern_
- Exclude files matching glob pattern.
- --token _token_
- Authentication token for private repos.
- --quiet
- Suppress verbose output, print only final result.
- --flavor _hardware_
- Hardware for jobs: cpu-basic, t4-small, a10g-small, a100-large, etc.
- --timeout _duration_
- Job timeout with units: 30m, 2h, 1d.
- --help
- Display help for any command.
FAQ
What is the hf command used for?
hf (formerly huggingface-cli) is the official command-line interface for Hugging Face Hub. It provides direct terminal access to download models and datasets, upload files, manage repositories, run compute jobs, and interact with the ML community platform. The CLI follows a consistent hf resource action pattern. Files are cached locally in ~/.cache/huggingface/hub/ with smart deduplication. The download command supports partial downloads with --include/--exclude patterns and resumable transfers. hf jobs enables running code on Hugging Face infrastructure including GPUs (T4, A10G, A100) and TPUs, with Docker-like commands. Jobs support environment variables, secrets, scheduled execution, and UV scripts for self-contained Python tasks. Authentication is managed via hf auth login which stores tokens locally. Tokens can also be set via the HF_TOKEN environment variable for scripting.
How do I run a basic hf example?
Run `hf auth login` in a terminal, then adjust file names, paths, flags, or remote targets for your system.
What does --repo-type _type_ do in hf?
Repository type: model, dataset, or space.