# Quick start The [Hugging Face Hub](https://hf.co/) is the go-to place for sharing machine learning models, demos, datasets, and metrics. `huggingface_hub` library helps you interact with the Hub without leaving your development environment. You can create and manage repositories easily, download and upload files, and get useful model and dataset metadata from the Hub. ## Install the Hub library To get started, you should install the `huggingface_hub` library. You can install the library with `pip` or `conda`. With `pip`: ```bash pip install huggingface_hub ``` With `conda`: ```bash conda install -c conda-forge huggingface_hub ``` ## Download files from the Hub Repositories on the Hub are git version controlled, and users can download a single file or the whole repository. You can use the [`hf_hub_download`] function to download files. This function will download and cache a file on your local disk. The next time you need that file, it will load from your cache, so you don't need to re-download it. You will need the repository id and the filename of the file you want to download. For example, to download the [Pegasus](https://huggingface.co/google/pegasus-xsum) model configuration file: ```py >>> from huggingface_hub import hf_hub_download >>> hf_hub_download(repo_id="google/pegasus-xsum", filename="config.json") ``` To download a specific version of the file, use the `revision` parameter to specify the branch name, tag, or commit hash. If you choose to use the commit hash, it must be the full-length hash instead of the shorter 7-character commit hash: ```py >>> from huggingface_hub import hf_hub_download >>> hf_hub_download( ... repo_id="google/pegasus-xsum", ... filename="config.json", ... revision="4d33b01d79672f27f001f6abade33f22d993b151" ... ) ``` For more details and options, see the API reference for [`hf_hub_download`]. ## Create a repository To create and share files to the Hub, you need to have a Hugging Face account. [Create an account](https://hf.co/join) if you don't already have one, and then sign in to find your [User Access Token](https://huggingface.co/docs/hub/security-tokens) in your Settings. The User Access Token is used to authenticate your identity to the Hub. You can also provide your token to our functions and methods. This way you don't need to store your token anywhere. 1. Log in to your Hugging Face account with the following command: ```bash huggingface-cli login ``` Or if you prefer to work from a Jupyter or Colaboratory notebook, then login with [`notebook_login`]: ```py >>> from huggingface_hub import notebook_login >>> notebook_login() ``` 2. Enter your User Access Token to authenticate your identity to the Hub. After you've created an account, create a repository with the [`create_repo`] function: ```py >>> from huggingface_hub import HfApi >>> api = HfApi() >>> api.create_repo(repo_id="super-cool-model") ``` If you want your repository to be private, then: ```py >>> from huggingface_hub import HfApi >>> api = HfApi() >>> api.create_repo(repo_id="super-cool-model", private=True) ``` Private repositories will not be visible to anyone except yourself. ## Share files to the Hub Use the [`upload_file`] function to add a file to your newly created repository. You need to specify: 1. The path of the file to upload. 2. The path of the file in the repository. 3. The repository id of where you want to add the file. ```py >>> from huggingface_hub import HfApi >>> api = HfApi() >>> api.upload_file(path_or_fileobj="/home/lysandre/dummy-test/README.md", ... path_in_repo="README.md", ... repo_id="lysandre/test-model", ... ) ``` To upload more than one file at a time, take a look at this [guide](how-to-upstream) which will introduce you to several methods for uploading files (with or without git). ## Next steps The `huggingface_hub` library provides an easy way for users to interact with the Hub with Python. To learn more about how you can manage your files and repositories on the Hub, we recommend reading our how-to guides for how to: - [Create and manage repositories](how-to-manage). - [Download](how-to-downstream) files from the Hub. - [Upload](how-to-upstream) files to the Hub. - [Search the Hub](searching-the-hub) for your desired model or dataset. - [Access the Inference API](how-to-inference) for fast inference.