diff --git a/docs/hub/academia-hub.md b/docs/hub/academia-hub.md index d8345e9a7d..d17afa3b79 100644 --- a/docs/hub/academia-hub.md +++ b/docs/hub/academia-hub.md @@ -1,8 +1,7 @@ # Academia Hub - -Ask your university's IT or Procurement Team to get in touch from a university-affiliated email address to initiate the subscription process. - +> [!TIP] +> Ask your university's IT or Procurement Team to get in touch from a university-affiliated email address to initiate the subscription process. Academia Hub is a paid offering that provides the Hugging Face Hub’s PRO features to every student, researcher, or faculty member of an academic institution. Explore advanced tools, enhanced collaboration, and exclusive resources to accelerate your learning, research, and teaching. The Hugging Face team is able to work with your IT or procurement department to set the product up. diff --git a/docs/hub/advanced-compute-options.md b/docs/hub/advanced-compute-options.md index 98562e829f..7bf2672fcc 100644 --- a/docs/hub/advanced-compute-options.md +++ b/docs/hub/advanced-compute-options.md @@ -1,8 +1,7 @@ # Advanced Compute Options - -This feature is part of the Team & Enterprise plans. - +> [!WARNING] +> This feature is part of the Team & Enterprise plans. Enterprise Hub organizations gain access to advanced compute options to accelerate their machine learning journey. diff --git a/docs/hub/agents.md b/docs/hub/agents.md index d5b6cafa20..ef968d5a34 100644 --- a/docs/hub/agents.md +++ b/docs/hub/agents.md @@ -18,11 +18,8 @@ With the HF MCP Server, you can enhance your AI assistant's capabilities by conn Visit [huggingface.co/settings/mcp](https://huggingface.co/settings/mcp) to configure your MCP client and get started. Read the dedicated one‑page guide: [HF MCP Server](./hf-mcp-server). - - -This feature is experimental ⚗️ and will continue to evolve. - - +> [!WARNING] +> This feature is experimental ⚗️ and will continue to evolve. ## tiny-agents (JS and Python) @@ -143,11 +140,8 @@ To use a local LLM (such as [llama.cpp](https://github.com/ggerganov/llama.cpp), Optionally, add a `PROMPT.md` to customize the system prompt. - - -Don't hesitate to contribute your agent to the community by opening a Pull Request in the [tiny-agents](https://huggingface.co/datasets/tiny-agents/tiny-agents) Hugging Face dataset. - - +> [!TIP] +> Don't hesitate to contribute your agent to the community by opening a Pull Request in the [tiny-agents](https://huggingface.co/datasets/tiny-agents/tiny-agents) Hugging Face dataset. ## Gradio MCP Server / Tools diff --git a/docs/hub/api.md b/docs/hub/api.md index fe24656725..ef6665206b 100644 --- a/docs/hub/api.md +++ b/docs/hub/api.md @@ -27,9 +27,8 @@ All API calls are subject to the HF-wide [Rate limits](./rate-limits). Upgrade y The following endpoints help get information about models, datasets, and Spaces stored on the Hub. - -When making API calls to retrieve information about repositories, the createdAt attribute indicates the time when the respective repository was created. It's important to note that there is a unique value, 2022-03-02T23:29:04.000Z assigned to all repositories that were created before we began storing creation dates. - +> [!TIP] +> When making API calls to retrieve information about repositories, the createdAt attribute indicates the time when the respective repository was created. It's important to note that there is a unique value, 2022-03-02T23:29:04.000Z assigned to all repositories that were created before we began storing creation dates. ### GET /api/models @@ -486,11 +485,8 @@ If no parameter is set, all collections are returned. The response is paginated. To get all collections, you must follow the [`Link` header](https://docs.github.com/en/rest/guides/using-pagination-in-the-rest-api?apiVersion=2022-11-28#link-header). - - -When listing collections, the item list per collection is truncated to 4 items maximum. To retrieve all items from a collection, you need to make an additional call using its collection slug. - - +> [!WARNING] +> When listing collections, the item list per collection is truncated to 4 items maximum. To retrieve all items from a collection, you need to make an additional call using its collection slug. Payload: diff --git a/docs/hub/audit-logs.md b/docs/hub/audit-logs.md index dbac851dd3..8cba2f13be 100644 --- a/docs/hub/audit-logs.md +++ b/docs/hub/audit-logs.md @@ -1,8 +1,7 @@ # Audit Logs - -This feature is part of the Team & Enterprise plans. - +> [!WARNING] +> This feature is part of the Team & Enterprise plans. Audit Logs enable organization admins to easily review actions taken by members, including organization membership, repository settings and billing changes. diff --git a/docs/hub/datasets-duckdb-combine-and-export.md b/docs/hub/datasets-duckdb-combine-and-export.md index 50240371a0..71f3c1df0b 100644 --- a/docs/hub/datasets-duckdb-combine-and-export.md +++ b/docs/hub/datasets-duckdb-combine-and-export.md @@ -84,13 +84,10 @@ SELECT COUNT(*) FROM 'output.parquet'; ``` - - -You can also export to [CSV](https://duckdb.org/docs/guides/file_formats/csv_export), [Excel](https://duckdb.org/docs/guides/file_formats/excel_export -) and [JSON](https://duckdb.org/docs/guides/file_formats/json_export -) formats. - - +> [!TIP] +> You can also export to [CSV](https://duckdb.org/docs/guides/file_formats/csv_export), [Excel](https://duckdb.org/docs/guides/file_formats/excel_export +> ) and [JSON](https://duckdb.org/docs/guides/file_formats/json_export +> ) formats. Finally, let's push the resulting dataset to the Hub. You can use the Hub UI, the `huggingface_hub` client library and more to upload your Parquet file, see more information [here](./datasets-adding). diff --git a/docs/hub/datasets-duckdb-sql.md b/docs/hub/datasets-duckdb-sql.md index 8cbab28d7b..a8484fbf7d 100644 --- a/docs/hub/datasets-duckdb-sql.md +++ b/docs/hub/datasets-duckdb-sql.md @@ -152,8 +152,5 @@ Finally, lets highlight some of the DuckDB functions used in this section: - `regexp_replace`, if the string contains the regexp pattern, replaces the matching part with replacement. - `LENGTH`, gets the number of characters in the string. - - -There are plenty of useful functions available in DuckDB's [SQL functions overview](https://duckdb.org/docs/sql/functions/overview). The best part is that you can use them directly on Hugging Face datasets. - - +> [!TIP] +> There are plenty of useful functions available in DuckDB's [SQL functions overview](https://duckdb.org/docs/sql/functions/overview). The best part is that you can use them directly on Hugging Face datasets. diff --git a/docs/hub/datasets-duckdb.md b/docs/hub/datasets-duckdb.md index f93bf3cedf..7cfef9191c 100644 --- a/docs/hub/datasets-duckdb.md +++ b/docs/hub/datasets-duckdb.md @@ -10,11 +10,8 @@ You can use the Hugging Face paths (`hf://`) to access data on the Hub: The [DuckDB CLI](https://duckdb.org/docs/api/cli/overview.html) (Command Line Interface) is a single, dependency-free executable. There are also other APIs available for running DuckDB, including Python, C++, Go, Java, Rust, and more. For additional details, visit their [clients](https://duckdb.org/docs/api/overview.html) page. - - -For installation details, visit the [installation page](https://duckdb.org/docs/installation). - - +> [!TIP] +> For installation details, visit the [installation page](https://duckdb.org/docs/installation). Starting from version `v0.10.3`, the DuckDB CLI includes native support for accessing datasets on the Hugging Face Hub via URLs with the `hf://` scheme. Here are some features you can leverage with this powerful tool: @@ -45,23 +42,20 @@ hf://datasets/{my-username}/{my-dataset}/{path_to_file} - **path_to_parquet_file**, the parquet file path which supports glob patterns, e.g `**/*.parquet`, to query all parquet files - - -You can query auto-converted Parquet files using the @~parquet branch, which corresponds to the `refs/convert/parquet` revision. For more details, refer to the documentation at https://huggingface.co/docs/datasets-server/en/parquet#conversion-to-parquet. - -To reference the `refs/convert/parquet` revision of a dataset, use the following syntax: - -```plaintext -hf://datasets/{my-username}/{my-dataset}@~parquet/{path_to_file} -``` - -Here is a sample URL following the above syntax: - -```plaintext -hf://datasets/ibm/duorc@~parquet/ParaphraseRC/test/0000.parquet -``` - - +> [!TIP] +> You can query auto-converted Parquet files using the @~parquet branch, which corresponds to the `refs/convert/parquet` revision. For more details, refer to the documentation at https://huggingface.co/docs/datasets-server/en/parquet#conversion-to-parquet. +> +> To reference the `refs/convert/parquet` revision of a dataset, use the following syntax: +> +> ```plaintext +> hf://datasets/{my-username}/{my-dataset}@~parquet/{path_to_file} +> ``` +> +> Here is a sample URL following the above syntax: +> +> ```plaintext +> hf://datasets/ibm/duorc@~parquet/ParaphraseRC/test/0000.parquet +> ``` Let's start with a quick demo to query all the rows of a dataset: diff --git a/docs/hub/datasets-gated.md b/docs/hub/datasets-gated.md index 8ea01b38ac..1f915bdd8b 100644 --- a/docs/hub/datasets-gated.md +++ b/docs/hub/datasets-gated.md @@ -147,11 +147,8 @@ By clicking on **Agree**, you agree to share your username and email address wit Once the access request is sent, there are two possibilities. If the approval mechanism is automatic, you immediately get access to the dataset files. Otherwise, the requests have to be approved manually by the authors, which can take more time. - - -The dataset authors have complete control over dataset access. In particular, they can decide at any time to block your access to the dataset without prior notice, regardless of approval mechanism or if your request has already been approved. - - +> [!WARNING] +> The dataset authors have complete control over dataset access. In particular, they can decide at any time to block your access to the dataset without prior notice, regardless of approval mechanism or if your request has already been approved. ### Download files diff --git a/docs/hub/datasets-manual-configuration.md b/docs/hub/datasets-manual-configuration.md index d71b0ec57f..ea3899e4a8 100644 --- a/docs/hub/datasets-manual-configuration.md +++ b/docs/hub/datasets-manual-configuration.md @@ -73,11 +73,8 @@ configs: --- ``` - - -Note that `config_name` field is required even if you have a single subset. - - +> [!WARNING] +> Note that `config_name` field is required even if you have a single subset. ## Multiple Subsets @@ -105,19 +102,16 @@ configs: Note that the order of subsets shown in the viewer is the default one first, then alphabetical. - - -You can set a default subset using `default: true` - -```yaml -- config_name: main_data - data_files: "main_data.csv" - default: true -``` - -This is useful to set which subset the Dataset Viewer shows first, and which subset data libraries load by default. - - +> [!TIP] +> You can set a default subset using `default: true` +> +> ```yaml +> - config_name: main_data +> data_files: "main_data.csv" +> default: true +> ``` +> +> This is useful to set which subset the Dataset Viewer shows first, and which subset data libraries load by default. ## Builder parameters diff --git a/docs/hub/datasets-pandas.md b/docs/hub/datasets-pandas.md index b4abd5293f..5510461bda 100644 --- a/docs/hub/datasets-pandas.md +++ b/docs/hub/datasets-pandas.md @@ -187,11 +187,8 @@ df["audio"] = df["audio"].sf.write() You can use `transformers` pipelines on pandas DataFrames to classify, generate text, images, etc. This section shows a few examples with `tqdm` for progress bars. - - -Pipelines don't accept a `tqdm` object as input but you can use a python generator instead, in the form `x for x in tqdm(...)` - - +> [!TIP] +> Pipelines don't accept a `tqdm` object as input but you can use a python generator instead, in the form `x for x in tqdm(...)` ### Text Classification diff --git a/docs/hub/datasets-polars.md b/docs/hub/datasets-polars.md index 9e19972a2a..7ed72e7392 100644 --- a/docs/hub/datasets-polars.md +++ b/docs/hub/datasets-polars.md @@ -26,11 +26,8 @@ import polars as pl pl.read_parquet("hf://datasets/roneneldan/TinyStories/data/train-00000-of-00004-2d5a1467fff1081b.parquet") ``` - - -Polars provides two APIs: a lazy API (`scan_parquet`) and an eager API (`read_parquet`). We recommend using the eager API for interactive workloads and the lazy API for performance as it allows for better query optimization. For more information on the topic, check out the [Polars user guide](https://docs.pola.rs/user-guide/concepts/lazy-api/#when-to-use-which). - - +> [!TIP] +> Polars provides two APIs: a lazy API (`scan_parquet`) and an eager API (`read_parquet`). We recommend using the eager API for interactive workloads and the lazy API for performance as it allows for better query optimization. For more information on the topic, check out the [Polars user guide](https://docs.pola.rs/user-guide/concepts/lazy-api/#when-to-use-which). Polars supports globbing to download multiple files at once into a single DataFrame. diff --git a/docs/hub/datasets-pyarrow.md b/docs/hub/datasets-pyarrow.md index f81b37d8e6..f554493210 100644 --- a/docs/hub/datasets-pyarrow.md +++ b/docs/hub/datasets-pyarrow.md @@ -81,13 +81,10 @@ pq.write_table(table_test , "hf://datasets/username/my_dataset/test.parquet", us We use `use_content_defined_chunking=True` to enable faster uploads and downloads from Hugging Face thanks to Xet deduplication (it requires `pyarrow>=21.0`). - - -Content defined chunking (CDC) makes the Parquet writer chunk the data pages in a way that makes duplicate data chunked and compressed identically. -Without CDC, the pages are arbitrarily chunked and therefore duplicate data are impossible to detect because of compression. -Thanks to CDC, Parquet uploads and downloads from Hugging Face are faster, since duplicate data are uploaded or downloaded only once. - - +> [!TIP] +> Content defined chunking (CDC) makes the Parquet writer chunk the data pages in a way that makes duplicate data chunked and compressed identically. +> Without CDC, the pages are arbitrarily chunked and therefore duplicate data are impossible to detect because of compression. +> Thanks to CDC, Parquet uploads and downloads from Hugging Face are faster, since duplicate data are uploaded or downloaded only once. Find more information about Xet [here](https://huggingface.co/join/xet). diff --git a/docs/hub/datasets-upload-guide-llm.md b/docs/hub/datasets-upload-guide-llm.md index 2389f52a6a..0cd949b036 100644 --- a/docs/hub/datasets-upload-guide-llm.md +++ b/docs/hub/datasets-upload-guide-llm.md @@ -1,8 +1,7 @@ # Hugging Face Dataset Upload Decision Guide - -This guide is primarily designed for LLMs to help users upload datasets to the Hugging Face Hub in the most compatible format. Users can also reference this guide to understand the upload process and best practices. - +> [!TIP] +> This guide is primarily designed for LLMs to help users upload datasets to the Hugging Face Hub in the most compatible format. Users can also reference this guide to understand the upload process and best practices. > Decision guide for uploading datasets to Hugging Face Hub. Optimized for Dataset Viewer compatibility and integration with the Hugging Face ecosystem. diff --git a/docs/hub/datasets-viewer-sql-console.md b/docs/hub/datasets-viewer-sql-console.md index af4afee68f..16a158c6ff 100644 --- a/docs/hub/datasets-viewer-sql-console.md +++ b/docs/hub/datasets-viewer-sql-console.md @@ -20,9 +20,8 @@ Through the SQL Console, you can: - Embed the results of the query in your own webpage using an iframe - Query datasets with natural language - -You can also use the DuckDB locally through the CLI to query the dataset via the `hf://` protocol. See the DuckDB Datasets documentation for more information. The SQL Console provides a convenient `Copy to DuckDB CLI` button that generates the SQL query for creating views and executing your query in the DuckDB CLI. - +> [!TIP] +> You can also use the DuckDB locally through the CLI to query the dataset via the `hf://` protocol. See the DuckDB Datasets documentation for more information. The SQL Console provides a convenient `Copy to DuckDB CLI` button that generates the SQL query for creating views and executing your query in the DuckDB CLI. ## Examples diff --git a/docs/hub/datasets-viewer.md b/docs/hub/datasets-viewer.md index 212124593c..415ff55012 100644 --- a/docs/hub/datasets-viewer.md +++ b/docs/hub/datasets-viewer.md @@ -58,11 +58,8 @@ In this case, an informational message lets you know that the Viewer is partial. To power the dataset viewer, the first 5GB of every dataset are auto-converted to the Parquet format (unless it was already a Parquet dataset). In the dataset viewer (for example, see [GLUE](https://huggingface.co/datasets/nyu-mll/glue)), you can click on [_"Auto-converted to Parquet"_](https://huggingface.co/datasets/nyu-mll/glue/tree/refs%2Fconvert%2Fparquet/cola) to access the Parquet files. Please, refer to the [dataset viewer docs](/docs/datasets-server/parquet_process) to learn how to query the dataset parquet files with libraries such as Polars, Pandas or DuckDB. - - -Parquet is a columnar storage format optimized for querying and processing large datasets. Parquet is a popular choice for big data processing and analytics and is widely used for data processing and machine learning. You can learn more about the advantages associated with this format in the documentation. - - +> [!TIP] +> Parquet is a columnar storage format optimized for querying and processing large datasets. Parquet is a popular choice for big data processing and analytics and is widely used for data processing and machine learning. You can learn more about the advantages associated with this format in the documentation. ### Conversion bot diff --git a/docs/hub/dduf.md b/docs/hub/dduf.md index bd887c9844..755241b145 100644 --- a/docs/hub/dduf.md +++ b/docs/hub/dduf.md @@ -14,13 +14,10 @@ This work draws inspiration from the [GGUF](https://github.com/ggerganov/ggml/bl Check out the [DDUF](https://huggingface.co/DDUF) org to start using some of the most popular diffusion models in DDUF. - - -We welcome contributions with open arms! - -To create a widely adopted file format, we need early feedback from the community. Nothing is set in stone, and we value everyone's input. Is your use case not covered? Please let us know in the DDUF organization [discussions](https://huggingface.co/spaces/DDUF/README/discussions/2). - - +> [!TIP] +> We welcome contributions with open arms! +> +> To create a widely adopted file format, we need early feedback from the community. Nothing is set in stone, and we value everyone's input. Is your use case not covered? Please let us know in the DDUF organization [discussions](https://huggingface.co/spaces/DDUF/README/discussions/2). Its key features include the following. diff --git a/docs/hub/enterprise-hub-advanced-security.md b/docs/hub/enterprise-hub-advanced-security.md index 4d8ed70e60..5509e27a2d 100644 --- a/docs/hub/enterprise-hub-advanced-security.md +++ b/docs/hub/enterprise-hub-advanced-security.md @@ -1,8 +1,7 @@ # Advanced Security - -This feature is part of the Team & Enterprise plans. - +> [!WARNING] +> This feature is part of the Team & Enterprise plans. Enterprise Hub organizations can improve their security with advanced security controls for both members and repositories. diff --git a/docs/hub/enterprise-hub-advanced-sso.md b/docs/hub/enterprise-hub-advanced-sso.md index d634dacb62..9cfee1133b 100644 --- a/docs/hub/enterprise-hub-advanced-sso.md +++ b/docs/hub/enterprise-hub-advanced-sso.md @@ -1,8 +1,7 @@ # Advanced Single Sign-On (SSO) - -This feature is part of the Enterprise Plus plan. - +> [!WARNING] +> This feature is part of the Enterprise Plus plan. Advanced Single Sign-On (SSO) capabilities extend the standard [SSO features](./security-sso) available in the Enterprise Hub, offering enhanced control and automation for user management and access across the entire Hugging Face platform for your organization members. @@ -34,9 +33,8 @@ This feature is particularly beneficial for organizations requiring a higher deg ## Limitations on Managed User Accounts - -Important Considerations for Managed Accounts. - +> [!WARNING] +> Important Considerations for Managed Accounts. To ensure organizational control and data governance, user accounts provisioned and managed via Advanced SSO ("managed user accounts") have specific limitations: diff --git a/docs/hub/enterprise-hub-analytics.md b/docs/hub/enterprise-hub-analytics.md index 99299649f8..2727e2c0d0 100644 --- a/docs/hub/enterprise-hub-analytics.md +++ b/docs/hub/enterprise-hub-analytics.md @@ -1,8 +1,7 @@ # Analytics - -This feature is part of the Team & Enterprise plans. - +> [!WARNING] +> This feature is part of the Team & Enterprise plans. ## Publisher Analytics Dashboard diff --git a/docs/hub/enterprise-hub-datasets.md b/docs/hub/enterprise-hub-datasets.md index 5ac3e86ebd..7071e9b0d7 100644 --- a/docs/hub/enterprise-hub-datasets.md +++ b/docs/hub/enterprise-hub-datasets.md @@ -1,8 +1,7 @@ # Datasets - -This feature is part of the Team & Enterprise plans. - +> [!WARNING] +> This feature is part of the Team & Enterprise plans. Data Studio is enabled on private datasets under your Enterprise Hub organization. diff --git a/docs/hub/enterprise-hub-gating-group-collections.md b/docs/hub/enterprise-hub-gating-group-collections.md index 1e1a1769c9..69989372fe 100644 --- a/docs/hub/enterprise-hub-gating-group-collections.md +++ b/docs/hub/enterprise-hub-gating-group-collections.md @@ -1,8 +1,7 @@ # Gating Group Collections - -This feature is part of the Team & Enterprise plans. - +> [!WARNING] +> This feature is part of the Team & Enterprise plans. Gating Group Collections allow organizations to grant (or reject) access to all the models and datasets in a collection at once, rather than per repo. Users will only have to go through **a single access request**. @@ -13,9 +12,8 @@ To enable Gating Group in a collection: - all models and datasets in the collection must be owned by the same organization as the collection - each model or dataset in the collection may only belong to one Gating Group Collection (but they can still be included in non-gating i.e. _regular_ collections). - -Gating only applies to models and datasets; any other resource part of the collection (such as a Space or a Paper) won't be affected. - +> [!TIP] +> Gating only applies to models and datasets; any other resource part of the collection (such as a Space or a Paper) won't be affected. ## Manage gating group as an organization admin @@ -140,9 +138,8 @@ Visit our [gated models](https://huggingface.co/docs/hub/models-gated#download-a Organizations can customize the gating parameters as well as the user information that is collected per gated repo. Please, visit our [gated models](https://huggingface.co/docs/hub/models-gated#customize-requested-information) or [gated datasets](https://huggingface.co/docs/hub/datasets-gated#customize-requested-information) documentation for more details. - -There is currently no way to customize the gate parameters and requested information in a centralized way. If you want to collect the same data no matter which collection's repository a user requests access throughout, you need to add the same gate parameters in the metadata of all the models and datasets of the collection, and keep it synced. - +> [!WARNING] +> There is currently no way to customize the gate parameters and requested information in a centralized way. If you want to collect the same data no matter which collection's repository a user requests access throughout, you need to add the same gate parameters in the metadata of all the models and datasets of the collection, and keep it synced. ## Access gated repos in a Gating Group Collection as a user diff --git a/docs/hub/enterprise-hub-network-security.md b/docs/hub/enterprise-hub-network-security.md index 285114950e..1f39fd456b 100644 --- a/docs/hub/enterprise-hub-network-security.md +++ b/docs/hub/enterprise-hub-network-security.md @@ -1,8 +1,7 @@ # Network Security - -This feature is part of the Enterprise Plus plan. - +> [!WARNING] +> This feature is part of the Enterprise Plus plan. ## Define your organization IP Ranges diff --git a/docs/hub/enterprise-hub-resource-groups.md b/docs/hub/enterprise-hub-resource-groups.md index cddf076fd9..19cfdaa5b6 100644 --- a/docs/hub/enterprise-hub-resource-groups.md +++ b/docs/hub/enterprise-hub-resource-groups.md @@ -1,8 +1,7 @@ # Resource groups - -This feature is part of the Team & Enterprise plans. - +> [!WARNING] +> This feature is part of the Team & Enterprise plans. Resource Groups allow organizations to enforce fine-grained access control to their repositories. diff --git a/docs/hub/enterprise-hub-scim.md b/docs/hub/enterprise-hub-scim.md index 9fb77693fd..25229f851c 100644 --- a/docs/hub/enterprise-hub-scim.md +++ b/docs/hub/enterprise-hub-scim.md @@ -1,8 +1,7 @@ # User Provisioning (SCIM) - -This feature is part of the Enterprise Plus plan. - +> [!WARNING] +> This feature is part of the Enterprise Plus plan. SCIM, or System for Cross-domain Identity Management, is a standard for automating user provisioning. It allows you to connect your Identity Provider (IdP) to Hugging Face to automatically manage your organization's members. diff --git a/docs/hub/enterprise-hub-tokens-management.md b/docs/hub/enterprise-hub-tokens-management.md index 6b47af0ea3..f1f20059c1 100644 --- a/docs/hub/enterprise-hub-tokens-management.md +++ b/docs/hub/enterprise-hub-tokens-management.md @@ -1,8 +1,7 @@ # Tokens Management - -This feature is part of the Team & Enterprise plans. - +> [!WARNING] +> This feature is part of the Team & Enterprise plans. Tokens Management enables organization administrators to oversee access tokens within their organization, ensuring secure access to organization resources. diff --git a/docs/hub/enterprise-hub.md b/docs/hub/enterprise-hub.md index c777fdec3e..69cd8c9f6d 100644 --- a/docs/hub/enterprise-hub.md +++ b/docs/hub/enterprise-hub.md @@ -1,8 +1,7 @@ # Team & Enterprise plans - -Subscribe to a Team or Enterprise plan to get access to advanced features for your organization. - +> [!TIP] +> Subscribe to a Team or Enterprise plan to get access to advanced features for your organization. Team & Enterprise organization plans add advanced capabilities to organizations, enabling safe, compliant and managed collaboration for companies and teams on Hugging Face. diff --git a/docs/hub/enterprise-sso.md b/docs/hub/enterprise-sso.md index 1dabde56ec..7aaf787037 100644 --- a/docs/hub/enterprise-sso.md +++ b/docs/hub/enterprise-sso.md @@ -1,8 +1,7 @@ # Single Sign-On (SSO) - -This feature is part of the Team & Enterprise plans. - +> [!WARNING] +> This feature is part of the Team & Enterprise plans. Single sign-on (SSO) allows organizations to securely manage user authentication through their own identity provider (IdP). Both SAML 2.0 and OpenID Connect (OIDC) protocols are supported. diff --git a/docs/hub/hf-mcp-server.md b/docs/hub/hf-mcp-server.md index 9ace12423a..bb3d5b4d1c 100644 --- a/docs/hub/hf-mcp-server.md +++ b/docs/hub/hf-mcp-server.md @@ -16,11 +16,8 @@ The Hugging Face MCP (Model Context Protocol) Server connects your MCP‑compati 3. Paste and restart: copy the snippet into your client’s MCP configuration, save, and restart/reload the client. You should see “Hugging Face” (or similar) listed as a connected MCP server in your client. - - -The settings page generates the exact configuration your client expects. Use it rather than writing config by hand. - - +> [!TIP] +> The settings page generates the exact configuration your client expects. Use it rather than writing config by hand. ![MCP Settings Example](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hf-mcp-settings.png) diff --git a/docs/hub/keras.md b/docs/hub/keras.md index cbedd8b1ce..64fc0ae996 100644 --- a/docs/hub/keras.md +++ b/docs/hub/keras.md @@ -44,11 +44,8 @@ If the repository does not exist on the Hub, it will be created for you. The upl By default, the repository will contain a minimal model card. Check out the [Model Card guide](https://huggingface.co/docs/hub/model-cards) to learn more about model cards and how to complete them. You can also programmatically update model cards using `huggingface_hub.ModelCard` (see [guide](https://huggingface.co/docs/huggingface_hub/guides/model-cards)). - - -You might be already familiar with `.keras` files. In fact, a `.keras` file is simply a zip file containing the `.json` and `model.weights.h5` files. When pushed to the Hub, the model is saved as an unzipped folder in order to let you navigate through the files. Note that if you manually upload a `.keras` file to a model repository on the Hub, the repository will automatically be tagged as `keras` but you won't be able to load it using `keras.saving.load_model`. - - +> [!TIP] +> You might be already familiar with `.keras` files. In fact, a `.keras` file is simply a zip file containing the `.json` and `model.weights.h5` files. When pushed to the Hub, the model is saved as an unzipped folder in order to let you navigate through the files. Note that if you manually upload a `.keras` file to a model repository on the Hub, the repository will automatically be tagged as `keras` but you won't be able to load it using `keras.saving.load_model`. ## Additional resources diff --git a/docs/hub/local-apps.md b/docs/hub/local-apps.md index 81834863ab..a8232f8066 100644 --- a/docs/hub/local-apps.md +++ b/docs/hub/local-apps.md @@ -31,13 +31,10 @@ Local apps are applications that can run Hugging Face models directly on your ma The best way to check if a local app is supported is to go to the Local Apps settings and see if the app is listed. Here is a quick overview of some of the most popular local apps: - - -👨‍💻 To use these local apps, copy the snippets from the model card as above. - -👷 If you're building a local app, you can learn about integrating with the Hub in [this guide](https://huggingface.co/docs/hub/en/models-adding-libraries). - - +> [!TIP] +> 👨‍💻 To use these local apps, copy the snippets from the model card as above. +> +> 👷 If you're building a local app, you can learn about integrating with the Hub in [this guide](https://huggingface.co/docs/hub/en/models-adding-libraries). ### Llama.cpp diff --git a/docs/hub/model-card-landscape-analysis.md b/docs/hub/model-card-landscape-analysis.md index 06c758e280..afbe695c53 100644 --- a/docs/hub/model-card-landscape-analysis.md +++ b/docs/hub/model-card-landscape-analysis.md @@ -110,18 +110,12 @@ While some headings within model cards may differ between models, we grouped com - +> [!TIP] +> [Checkout the User Studies](./model-cards-user-studies) - [Checkout the User Studies](./model-cards-user-studies) - - - - - - [See Appendix](./model-card-appendix) - - +> [!TIP] +> [See Appendix](./model-card-appendix) [^1]: For each tool, descriptions are excerpted from the linked paper listed in the second column. diff --git a/docs/hub/model-cards-user-studies.md b/docs/hub/model-cards-user-studies.md index bf68dce1cb..2b72df3e54 100644 --- a/docs/hub/model-cards-user-studies.md +++ b/docs/hub/model-cards-user-studies.md @@ -97,11 +97,8 @@ We selected people from a variety of different backgrounds relevant to machine l ![user studies results 2](https://huggingface.co/datasets/huggingface/documentation-images/blob/main/hub/user-studies-responses(2).png) - - - [Checkout the Appendix](./model-card-appendix) - - +> [!TIP] +> [Checkout the Appendix](./model-card-appendix) Acknowledgements diff --git a/docs/hub/models-adding-libraries.md b/docs/hub/models-adding-libraries.md index ade70c7cfa..e99bcded6b 100644 --- a/docs/hub/models-adding-libraries.md +++ b/docs/hub/models-adding-libraries.md @@ -29,15 +29,12 @@ pip install huggingface_hub For more details about `huggingface_hub` installation, check out [this guide](https://huggingface.co/docs/huggingface_hub/installation). - - -In this guide, we will focus on Python libraries. If you've implemented your library in JavaScript, you can use [`@huggingface/hub`](https://www.npmjs.com/package/@huggingface/hub) instead. The rest of the logic (i.e. hosting files, code samples, etc.) does not depend on the code language. - -``` -npm add @huggingface/hub -``` - - +> [!TIP] +> In this guide, we will focus on Python libraries. If you've implemented your library in JavaScript, you can use [`@huggingface/hub`](https://www.npmjs.com/package/@huggingface/hub) instead. The rest of the logic (i.e. hosting files, code samples, etc.) does not depend on the code language. +> +> ``` +> npm add @huggingface/hub +> ``` Users will need to authenticate once they have successfully installed the `huggingface_hub` library. The easiest way to authenticate is to save the token on the machine. Users can do that from the terminal using the `login()` command: diff --git a/docs/hub/models-downloading.md b/docs/hub/models-downloading.md index d15eea1f46..dbc54081fe 100644 --- a/docs/hub/models-downloading.md +++ b/docs/hub/models-downloading.md @@ -59,13 +59,10 @@ pip install "huggingface_hub[hf_transfer]" HF_HUB_ENABLE_HF_TRANSFER=1 hf download ... ``` - - -`hf_transfer` is a power user tool! -It is tested and production-ready, -but it lacks user-friendly features like advanced error handling or proxies. -For more details, please take a look at this [guide](https://huggingface.co/docs/huggingface_hub/hf_transfer). - - +> [!WARNING] +> `hf_transfer` is a power user tool! +> It is tested and production-ready, +> but it lacks user-friendly features like advanced error handling or proxies. +> For more details, please take a look at this [guide](https://huggingface.co/docs/huggingface_hub/hf_transfer). diff --git a/docs/hub/models-gated.md b/docs/hub/models-gated.md index 2fdbdfb43c..26f27dc807 100644 --- a/docs/hub/models-gated.md +++ b/docs/hub/models-gated.md @@ -161,11 +161,8 @@ By clicking on **Agree**, you agree to share your username and email address wit Once the access request is sent, there are two possibilities. If the approval mechanism is automatic, you immediately get access to the model files. Otherwise, the requests have to be approved manually by the authors, which can take more time. - - -The model authors have complete control over model access. In particular, they can decide at any time to block your access to the model without prior notice, regardless of approval mechanism or if your request has already been approved. - - +> [!WARNING] +> The model authors have complete control over model access. In particular, they can decide at any time to block your access to the model without prior notice, regardless of approval mechanism or if your request has already been approved. ### Download files diff --git a/docs/hub/models-inference.md b/docs/hub/models-inference.md index a6d85060ec..7f0b4cc865 100644 --- a/docs/hub/models-inference.md +++ b/docs/hub/models-inference.md @@ -69,11 +69,8 @@ completion = client.chat.completions.create( ) ``` - - -The OpenAI API compatible client is not supported for image generation. - - +> [!WARNING] +> The OpenAI API compatible client is not supported for image generation. @@ -116,11 +113,8 @@ const completion = await client.chat.completions.create({ ``` - - -The OpenAI API compatible client is not supported for image generation. - - +> [!WARNING] +> The OpenAI API compatible client is not supported for image generation. diff --git a/docs/hub/moderation.md b/docs/hub/moderation.md index 4bc6ab85ba..ca019721bf 100644 --- a/docs/hub/moderation.md +++ b/docs/hub/moderation.md @@ -1,10 +1,7 @@ # Moderation - - -Check out the [Code of Conduct](https://huggingface.co/code-of-conduct) and the [Content Guidelines](https://huggingface.co/content-guidelines). - - +> [!TIP] +> Check out the [Code of Conduct](https://huggingface.co/code-of-conduct) and the [Content Guidelines](https://huggingface.co/content-guidelines). ## Reporting a repository diff --git a/docs/hub/oauth.md b/docs/hub/oauth.md index 778475d60d..5e68ea5454 100644 --- a/docs/hub/oauth.md +++ b/docs/hub/oauth.md @@ -18,11 +18,8 @@ You can create your application in your [settings](https://huggingface.co/settin ### If you are hosting in Spaces - - -If you host your app on Spaces, then the flow will be even easier to implement (and built-in to Gradio directly); Check our [Spaces OAuth guide](https://huggingface.co/docs/hub/spaces-oauth). - - +> [!TIP] +> If you host your app on Spaces, then the flow will be even easier to implement (and built-in to Gradio directly); Check our [Spaces OAuth guide](https://huggingface.co/docs/hub/spaces-oauth). ## Currently supported scopes @@ -40,11 +37,8 @@ The currently supported scopes are: All other information is available in the [OpenID metadata](https://huggingface.co/.well-known/openid-configuration). - - -Please contact us if you need any extra scopes. - - +> [!WARNING] +> Please contact us if you need any extra scopes. ## Accessing organization resources diff --git a/docs/hub/organizations-security.md b/docs/hub/organizations-security.md index db2289420d..d6e0969f51 100644 --- a/docs/hub/organizations-security.md +++ b/docs/hub/organizations-security.md @@ -1,18 +1,12 @@ # Access control in organizations - +> [!TIP] +> You can set up [Single Sign-On (SSO)](./security-sso) to be able to map access control rules from your organization's Identity Provider. -You can set up [Single Sign-On (SSO)](./security-sso) to be able to map access control rules from your organization's Identity Provider. - - - - - -Advanced and more fine-grained access control can be achieved with [Resource Groups](./security-resource-groups). - -The Resource Group feature is part of the Team & Enterprise plans. - - +> [!TIP] +> Advanced and more fine-grained access control can be achieved with [Resource Groups](./security-resource-groups). +> +> The Resource Group feature is part of the Team & Enterprise plans. Members of organizations can have four different roles: `read`, `contributor`, `write`, or `admin`: @@ -33,9 +27,8 @@ As an organization `admin`, go to the **Members** section of the org settings to ## Viewing members' email address - -This feature is part of the Team & Enterprise plans. - +> [!WARNING] +> This feature is part of the Team & Enterprise plans. You may be able to view the email addresses of members of your organization. The visibility of the email addresses depends on the organization's SSO configuration, or verified organization status. diff --git a/docs/hub/repositories-getting-started.md b/docs/hub/repositories-getting-started.md index 9e2c180ee2..fab8fd8e95 100644 --- a/docs/hub/repositories-getting-started.md +++ b/docs/hub/repositories-getting-started.md @@ -139,11 +139,8 @@ And you're done! You can check your repository on Hugging Face with all the rece - - -If you cloned the repository with HTTP, you might be asked to fill your username and password on every push operation. The simplest way to avoid repetition is to [switch to SSH](#cloning-repositories), instead of HTTP. Alternatively, if you have to use HTTP, you might find it helpful to setup a [git credential helper](https://git-scm.com/docs/gitcredentials#_avoiding_repetition) to autofill your username and password. - - +> [!TIP] +> If you cloned the repository with HTTP, you might be asked to fill your username and password on every push operation. The simplest way to avoid repetition is to [switch to SSH](#cloning-repositories), instead of HTTP. Alternatively, if you have to use HTTP, you might find it helpful to setup a [git credential helper](https://git-scm.com/docs/gitcredentials#_avoiding_repetition) to autofill your username and password. ## Viewing a repo's history diff --git a/docs/hub/security-2fa.md b/docs/hub/security-2fa.md index c6b9587910..96fa7d3fcd 100644 --- a/docs/hub/security-2fa.md +++ b/docs/hub/security-2fa.md @@ -35,9 +35,8 @@ In Hugging Face Hub: If you entered the correct pin, the Hub displays a list of recovery codes. Download them and keep them in a safe place. - -You will be prompted for 2FA every time you log in, and every 30 days - +> [!TIP] +> You will be prompted for 2FA every time you log in, and every 30 days ## Recovery codes @@ -60,9 +59,8 @@ To regenerate 2FA recovery codes: 2. If you’ve already configured 2FA, select Recovery Code 3. Click on Regenerate recovery codes - -If you regenerate 2FA recovery codes, save them. You can’t use any previously created recovery codes. - +> [!WARNING] +> If you regenerate 2FA recovery codes, save them. You can’t use any previously created recovery codes. ## Sign in with two-factor authentication enabled diff --git a/docs/hub/security-gpg.md b/docs/hub/security-gpg.md index 540c172c8d..cf773e99d4 100644 --- a/docs/hub/security-gpg.md +++ b/docs/hub/security-gpg.md @@ -88,6 +88,5 @@ git commit -S -m "My first signed commit" Once pushed on the Hub, you should see the commit with a "Verified" badge. - -To sign all commits by default in any local repository on your computer, you can run git config --global commit.gpgsign true. - +> [!TIP] +> To sign all commits by default in any local repository on your computer, you can run git config --global commit.gpgsign true. diff --git a/docs/hub/security-malware.md b/docs/hub/security-malware.md index aea1298bf9..caa2dd7e02 100644 --- a/docs/hub/security-malware.md +++ b/docs/hub/security-malware.md @@ -11,9 +11,8 @@ Here is an [example view](https://huggingface.co/mcpotato/42-eicar-street/tree/m - -If your file has neither an ok nor infected badge, it could mean that it is either currently being scanned, waiting to be scanned, or that there was an error during the scan. It can take up to a few minutes to be scanned. - +> [!TIP] +> If your file has neither an ok nor infected badge, it could mean that it is either currently being scanned, waiting to be scanned, or that there was an error during the scan. It can take up to a few minutes to be scanned. If at least one file has a been scanned as unsafe, a message will warn the users: @@ -26,6 +25,5 @@ If at least one file has a been scanned as unsafe, a message will warn the users - -As the repository owner, we advise you to remove the suspicious file. The repository will appear back as safe. - +> [!TIP] +> As the repository owner, we advise you to remove the suspicious file. The repository will appear back as safe. diff --git a/docs/hub/security-protectai.md b/docs/hub/security-protectai.md index 68f69b728b..277748e07b 100644 --- a/docs/hub/security-protectai.md +++ b/docs/hub/security-protectai.md @@ -1,8 +1,7 @@ # Third-party scanner: Protect AI - -Interested in joining our security partnership / providing scanning information on the Hub? Please get in touch with us over at security@huggingface.co.* - +> [!TIP] +> Interested in joining our security partnership / providing scanning information on the Hub? Please get in touch with us over at security@huggingface.co.* [Protect AI](https://protectai.com/)'s [Guardian](https://protectai.com/guardian) catches pickle, Keras, and other exploits as detailed on their [Knowledge Base page](https://protectai.com/insights/knowledge-base/). Guardian also benefits from reports sent in by their community of bounty [Huntr](https://huntr.com/)s. diff --git a/docs/hub/security-resource-groups.md b/docs/hub/security-resource-groups.md index c7a6b8f92c..48b72cbd11 100644 --- a/docs/hub/security-resource-groups.md +++ b/docs/hub/security-resource-groups.md @@ -1,8 +1,7 @@ # Advanced Access Control in Organizations with Resource Groups - -This feature is part of the Team & Enterprise plans. - +> [!WARNING] +> This feature is part of the Team & Enterprise plans. In your Hugging Face organization, you can use Resource Groups to control which members have access to specific repositories. diff --git a/docs/hub/security-sso-azure-oidc.md b/docs/hub/security-sso-azure-oidc.md index 5ba22798d1..a9a4ca45d4 100644 --- a/docs/hub/security-sso-azure-oidc.md +++ b/docs/hub/security-sso-azure-oidc.md @@ -2,9 +2,8 @@ This guide will use Azure as the SSO provider and the Open ID Connect (OIDC) protocol as our preferred identity protocol. - - This feature is part of the Team & Enterprise plans. - +> [!WARNING] +> This feature is part of the Team & Enterprise plans. ### Step 1: Create a new application in your Identity Provider diff --git a/docs/hub/security-sso-azure-saml.md b/docs/hub/security-sso-azure-saml.md index 97ba3c2be0..8f30c8042b 100644 --- a/docs/hub/security-sso-azure-saml.md +++ b/docs/hub/security-sso-azure-saml.md @@ -4,9 +4,8 @@ In this guide, we will use Azure as the SSO provider and with the Security Asser We currently support SP-initiated and IdP-initiated authentication. User provisioning is part of Enterprise Plus's [Advanced SSO](./enterprise-hub-advanced-sso). - - This feature is part of the Team & Enterprise plans. - +> [!WARNING] +> This feature is part of the Team & Enterprise plans. ### Step 1: Create a new application in your Identity Provider diff --git a/docs/hub/security-sso-entra-id-scim.md b/docs/hub/security-sso-entra-id-scim.md index 4a817bf90a..78825bab02 100644 --- a/docs/hub/security-sso-entra-id-scim.md +++ b/docs/hub/security-sso-entra-id-scim.md @@ -2,9 +2,8 @@ This guide explains how to set up automatic user and group provisioning between Microsoft Entra ID and your Hugging Face organization using SCIM. - -This feature is part of the Enterprise Plus plan. - +> [!WARNING] +> This feature is part of the Enterprise Plus plan. ### Step 1: Get SCIM configuration from Hugging Face @@ -54,16 +53,15 @@ This feature is part of the -

Active Directory Plan Considerations

- - +> [!TIP] +>

Active Directory Plan Considerations

+> ### Step 6: Verify Provisioning in Hugging Face diff --git a/docs/hub/security-sso-google-oidc.md b/docs/hub/security-sso-google-oidc.md index 6e0bae9e21..465a9492f2 100644 --- a/docs/hub/security-sso-google-oidc.md +++ b/docs/hub/security-sso-google-oidc.md @@ -4,9 +4,8 @@ In this guide, we will use Google Workspace as the SSO provider with the OpenID We currently support SP-initiated authentication. User provisioning is part of Enterprise Plus's [Advanced SSO](./enterprise-hub-advanced-sso). - - This feature is part of the Team & Enterprise plans. - +> [!WARNING] +> This feature is part of the Team & Enterprise plans. ### Step 1: Create OIDC App in Google Workspace @@ -35,9 +34,8 @@ We currently support SP-initiated authentication. User provisioning is part of E ### Step 3: Test and Enable SSO - -Before testing, ensure you have granted access to the application for the appropriate users. The admin performing the test must have access. - +> [!WARNING] +> Before testing, ensure you have granted access to the application for the appropriate users. The admin performing the test must have access. - Now, in your Hugging Face SSO settings, click on **"Update and Test OIDC configuration"**. - You should be redirected to your Google login prompt. Once logged in, you'll be redirected to your organization's settings page. diff --git a/docs/hub/security-sso-google-saml.md b/docs/hub/security-sso-google-saml.md index 2d57ca24ab..517a8c1a4c 100644 --- a/docs/hub/security-sso-google-saml.md +++ b/docs/hub/security-sso-google-saml.md @@ -4,9 +4,8 @@ In this guide, we will use Google Workspace as the SSO provider and with the Sec We currently support SP-initiated and IdP-initiated authentication. User provisioning is part of Enterprise Plus's [Advanced SSO](./enterprise-hub-advanced-sso). - - This feature is part of the Team & Enterprise plans. - +> [!WARNING] +> This feature is part of the Team & Enterprise plans. ### Step 1: Create SAML App in Google Workspace @@ -67,9 +66,8 @@ We currently support SP-initiated and IdP-initiated authentication. User provisi ### Step 5: Test and Enable SSO - -Before testing, ensure you have granted access to the application for the appropriate users in the Google Workspace admin console under the app's "User access" settings. The admin performing the test must have access. It may take a few minutes for user access changes to apply on Google Workspace. - +> [!WARNING] +> Before testing, ensure you have granted access to the application for the appropriate users in the Google Workspace admin console under the app's "User access" settings. The admin performing the test must have access. It may take a few minutes for user access changes to apply on Google Workspace. - Now, in your Hugging Face SSO settings, click on **"Update and Test SAML configuration"**. - You should be redirected to your Google login prompt. Once logged in, you'll be redirected to your organization's settings page. diff --git a/docs/hub/security-sso-okta-oidc.md b/docs/hub/security-sso-okta-oidc.md index 91979658b1..f716c870d4 100644 --- a/docs/hub/security-sso-okta-oidc.md +++ b/docs/hub/security-sso-okta-oidc.md @@ -2,9 +2,8 @@ In this guide, we will use Okta as the SSO provider and with the Open ID Connect (OIDC) protocol as our preferred identity protocol. - - This feature is part of the Team & Enterprise plans. - +> [!WARNING] +> This feature is part of the Team & Enterprise plans. ### Step 1: Create a new application in your Identity Provider diff --git a/docs/hub/security-sso-okta-saml.md b/docs/hub/security-sso-okta-saml.md index 69a9b3d988..12cb03aaba 100644 --- a/docs/hub/security-sso-okta-saml.md +++ b/docs/hub/security-sso-okta-saml.md @@ -4,9 +4,8 @@ In this guide, we will use Okta as the SSO provider and with the Security Assert We currently support SP-initiated and IdP-initiated authentication. User provisioning is part of Enterprise Plus's [Advanced SSO](./enterprise-hub-advanced-sso). - - This feature is part of the Team & Enterprise plans. - +> [!WARNING] +> This feature is part of the Team & Enterprise plans. ### Step 1: Create a new application in your Identity Provider diff --git a/docs/hub/security-sso-okta-scim.md b/docs/hub/security-sso-okta-scim.md index 042da4a3c1..d8045fb2ce 100644 --- a/docs/hub/security-sso-okta-scim.md +++ b/docs/hub/security-sso-okta-scim.md @@ -2,9 +2,8 @@ This guide explains how to set up SCIM user and group provisioning between Okta and your Hugging Face organization using SCIM. - -This feature is part of the Enterprise Plus plan. - +> [!WARNING] +> This feature is part of the Enterprise Plus plan. ### Step 1: Get SCIM configuration from Hugging Face @@ -54,16 +53,15 @@ This feature is part of the Team & Enterprise plans. For enhanced capabilities like automated user provisioning (JIT/SCIM) and global SSO enforcement, see our Advanced SSO documentation +> [!WARNING] +> This feature is part of the Team & Enterprise plans. For enhanced capabilities like automated user provisioning (JIT/SCIM) and global SSO enforcement, see our Advanced SSO documentation ## How does it work? diff --git a/docs/hub/security-tokens.md b/docs/hub/security-tokens.md index 7a3115a550..5054064edc 100644 --- a/docs/hub/security-tokens.md +++ b/docs/hub/security-tokens.md @@ -61,9 +61,8 @@ access_token = "hf_..." model = AutoModel.from_pretrained("private/model", token=access_token) ``` - -Try not to leak your token! Though you can always rotate it, anyone will be able to read or write your private repos in the meantime which is 💩 - +> [!WARNING] +> Try not to leak your token! Though you can always rotate it, anyone will be able to read or write your private repos in the meantime which is 💩 ### Best practices diff --git a/docs/hub/spaces-config-reference.md b/docs/hub/spaces-config-reference.md index 012529a2da..aa62ee4792 100644 --- a/docs/hub/spaces-config-reference.md +++ b/docs/hub/spaces-config-reference.md @@ -136,8 +136,5 @@ preload_from_hub: ``` In this example, the Space will preload specific .safetensors files from `warp-ai/wuerstchen-prior`, the complete `coqui/XTTS-v1` repository, and a specific revision of the `config.json` file in the `openai-community/gpt2` repository from the Hugging Face Hub during build time. - - -Files are saved in the default `huggingface_hub` disk cache `~/.cache/huggingface/hub`. If you application expects them elsewhere or you changed your `HF_HOME` variable, this pre-loading does not follow that at this time. - - +> [!WARNING] +> Files are saved in the default `huggingface_hub` disk cache `~/.cache/huggingface/hub`. If you application expects them elsewhere or you changed your `HF_HOME` variable, this pre-loading does not follow that at this time. diff --git a/docs/hub/spaces-cookie-limitations.md b/docs/hub/spaces-cookie-limitations.md index c3b0c57a2a..8fb1ae3e4b 100644 --- a/docs/hub/spaces-cookie-limitations.md +++ b/docs/hub/spaces-cookie-limitations.md @@ -19,6 +19,5 @@ To work around this issue, you would need to set the `server.enableXsrfProtectio enableXsrfProtection = false ``` - -When you are using the Streamlit SDK, you don't need to worry about this because the SDK does it for you. - +> [!TIP] +> When you are using the Streamlit SDK, you don't need to worry about this because the SDK does it for you. diff --git a/docs/hub/spaces-custom-domain.md b/docs/hub/spaces-custom-domain.md index e4081ee84d..6ad74e0422 100644 --- a/docs/hub/spaces-custom-domain.md +++ b/docs/hub/spaces-custom-domain.md @@ -1,9 +1,8 @@ # Spaces Custom Domain - -Spaces Custom Domain feature is part of PRO and Team or Enterprise subscriptions. - +> [!WARNING] +> Spaces Custom Domain feature is part of PRO and Team or Enterprise subscriptions. ## Getting started with a Custom Domain diff --git a/docs/hub/spaces-dev-mode.md b/docs/hub/spaces-dev-mode.md index ad93203863..b883ce2324 100644 --- a/docs/hub/spaces-dev-mode.md +++ b/docs/hub/spaces-dev-mode.md @@ -1,12 +1,10 @@ # Spaces Dev Mode: Seamless development in Spaces - -This feature is still in Beta stage. - +> [!WARNING] +> This feature is still in Beta stage. - -The Spaces Dev Mode is part of PRO or Team & Enterprise plans. - +> [!WARNING] +> The Spaces Dev Mode is part of PRO or Team & Enterprise plans. ## Spaces Dev Mode diff --git a/docs/hub/spaces-gpus.md b/docs/hub/spaces-gpus.md index 7dbe7efb97..95cb298e01 100644 --- a/docs/hub/spaces-gpus.md +++ b/docs/hub/spaces-gpus.md @@ -7,9 +7,8 @@ You can upgrade your Space to use a GPU accelerator using the _Settings_ button - -Longer-term, we would also like to expose non-GPU hardware, like HPU, IPU or TPU. If you have a specific AI hardware you'd like to run on, please let us know (website at huggingface.co). - +> [!TIP] +> Longer-term, we would also like to expose non-GPU hardware, like HPU, IPU or TPU. If you have a specific AI hardware you'd like to run on, please let us know (website at huggingface.co). As soon as your Space is running on GPU you can see which hardware it’s running on directly from this badge: diff --git a/docs/hub/spaces-mcp-servers.md b/docs/hub/spaces-mcp-servers.md index d30d050b4c..2cce7db9a5 100644 --- a/docs/hub/spaces-mcp-servers.md +++ b/docs/hub/spaces-mcp-servers.md @@ -9,9 +9,8 @@ From your [Hub MCP settings](https://huggingface.co/settings/mcp), select your M ![image/png](https://cdn-uploads.huggingface.co/production/uploads/5f17f0a0925b9863e28ad517/wWm_GeuWF17OrMyJT4tMx.png) - -You need a valid Hugging Face token with READ permissions to use MCP tools. If you don't have one, create a new "Read" access token here. - +> [!WARNING] +> You need a valid Hugging Face token with READ permissions to use MCP tools. If you don't have one, create a new "Read" access token here. ## Add an existing Space to your MCP tools @@ -28,9 +27,8 @@ You need a valid Hugging Face token with READ permissions to us If your MCP client is configured correctly, the Spaces you added will be available instantly without changing anything (if it doesn't restart your client and it should appear). Most MCP clients will list what tools are currently loaded so you can make sure the Space is available. - -For ZeroGPU Spaces, your quota will be used when the tool is called, if you run out of quota you can subscribe to PRO to get 25 minutes of daily quota (x8 more quota than free users). For example your PRO account lets you generate up to 600 images per day using FLUX.1-schnell. - +> [!TIP] +> For ZeroGPU Spaces, your quota will be used when the tool is called, if you run out of quota you can subscribe to PRO to get 25 minutes of daily quota (x8 more quota than free users). For example your PRO account lets you generate up to 600 images per day using FLUX.1-schnell. ## Build your own MCP-compatible Gradio Space @@ -67,9 +65,8 @@ demo.launch(mcp_server=True) # exposes an MCP schema automatically Push the app to a **Gradio Space** and it will automatically receive the **MCP** badge. Anyone can then add it as a tool with a single click. - -It's also quite easy to convert an existing Gradio Space to MCP server. Duplicate it from the context menu then just add the mcp_server=True parameter to your launch() method, and ensure your functions have clear type hints and docstrings - you can use AI tools to automate this quite easily (example of AI generated docstrings). - +> [!TIP] +> It's also quite easy to convert an existing Gradio Space to MCP server. Duplicate it from the context menu then just add the mcp_server=True parameter to your launch() method, and ensure your functions have clear type hints and docstrings - you can use AI tools to automate this quite easily (example of AI generated docstrings). ## Be creative by mixing Spaces! diff --git a/docs/hub/spaces-oauth.md b/docs/hub/spaces-oauth.md index 6e262762a9..f711a2c776 100644 --- a/docs/hub/spaces-oauth.md +++ b/docs/hub/spaces-oauth.md @@ -4,17 +4,11 @@ You can enable a built-in sign-in flow in your Space by seamlessly creating and This enables new use cases for your Space. For instance, when combined with [Persistent Storage](https://huggingface.co/docs/hub/spaces-storage), a generative AI Space could allow users to log in to access their previous generations, only accessible to them. - +> [!TIP] +> This guide will take you through the process of integrating a *Sign-In with HF* button into any Space. If you're seeking a fast and simple method to implement this in a **Gradio** Space, take a look at its [built-in integration](https://www.gradio.app/guides/sharing-your-app#o-auth-login-via-hugging-face). -This guide will take you through the process of integrating a *Sign-In with HF* button into any Space. If you're seeking a fast and simple method to implement this in a **Gradio** Space, take a look at its [built-in integration](https://www.gradio.app/guides/sharing-your-app#o-auth-login-via-hugging-face). - - - - - -You can also use the HF OAuth flow to create a "Sign in with HF" flow in any website or App, outside of Spaces. [Read our general OAuth page](./oauth). - - +> [!TIP] +> You can also use the HF OAuth flow to create a "Sign in with HF" flow in any website or App, outside of Spaces. [Read our general OAuth page](./oauth). ## Create an OAuth app @@ -104,11 +98,8 @@ Basically, you need to: - Handle the callback on `/auth/callback` or `/login/callback` (or your own custom callback URL) and verify the `state` parameter. - Use the `code` query parameter to get an access token and id token from `https://huggingface.co/oauth/token` (POST request with `client_id`, `code`, `grant_type=authorization_code` and `redirect_uri` as form data, and with `Authorization: Basic {base64(client_id:client_secret)}` as a header). - - -You should use `target=_blank` on the button to open the sign-in page in a new tab, unless you run the space outside its `iframe`. Otherwise, you might encounter issues with cookies on some browsers. - - +> [!WARNING] +> You should use `target=_blank` on the button to open the sign-in page in a new tab, unless you run the space outside its `iframe`. Otherwise, you might encounter issues with cookies on some browsers. ## Examples: diff --git a/docs/hub/spaces-sdks-docker-aim.md b/docs/hub/spaces-sdks-docker-aim.md index 099e2332ae..7aefb1b280 100644 --- a/docs/hub/spaces-sdks-docker-aim.md +++ b/docs/hub/spaces-sdks-docker-aim.md @@ -57,9 +57,8 @@ Here is what to expect: Filter your runs using Aim’s Pythonic search. You can write pythonic [queries against](https://aimstack.readthedocs.io/en/latest/using/search.html) EVERYTHING you have tracked - metrics, hyperparams etc. Check out some [examples](https://huggingface.co/aimstack) on HF Hub Spaces. - -Note that if your logs are in TensorBoard format, you can easily convert them to Aim with one command and use the many advanced and high-performant training run comparison features available. - +> [!TIP] +> Note that if your logs are in TensorBoard format, you can easily convert them to Aim with one command and use the many advanced and high-performant training run comparison features available. ## More on HF Spaces diff --git a/docs/hub/spaces-sdks-docker-giskard.md b/docs/hub/spaces-sdks-docker-giskard.md index b2a32dffd0..54773077c4 100644 --- a/docs/hub/spaces-sdks-docker-giskard.md +++ b/docs/hub/spaces-sdks-docker-giskard.md @@ -31,14 +31,11 @@ You can deploy Giskard on Spaces with just a few clicks: - - -IMPORTANT NOTE ABOUT DATA PERSISTENCE: -You can use the Giskard Space as is for initial exploration and experimentation. For **longer use in -small-scale projects, activate the [paid persistent storage option](https://huggingface.co/docs/hub/spaces-storage)**. This prevents data loss during Space restarts which -occur every 24 hours. - - +> [!WARNING] +> IMPORTANT NOTE ABOUT DATA PERSISTENCE: +> You can use the Giskard Space as is for initial exploration and experimentation. For **longer use in +> small-scale projects, activate the [paid persistent storage option](https://huggingface.co/docs/hub/spaces-storage)**. This prevents data loss during Space restarts which +> occur every 24 hours. You need to define the **Owner** (your personal account or an organization), a **Space name**, and the **Visibility**. If you don’t want to publicly share your models and quality tests, set your Space to **Private**. @@ -100,12 +97,9 @@ giskard worker start -d -k GISKARD-API-KEY -u https://XXX.hf.space --hf-token GI In order to start building quality tests for a project, you will need to upload model and dataset objects, and either create or upload a test suite from the Giskard Python library. - - -For more information on how to create test suites from Giskard's Python library's automated model scanning tool, head -over to Giskard's [Quickstart Guides](https://docs.giskard.ai/en/latest/getting_started/quickstart/index.html). - - +> [!TIP] +> For more information on how to create test suites from Giskard's Python library's automated model scanning tool, head +> over to Giskard's [Quickstart Guides](https://docs.giskard.ai/en/latest/getting_started/quickstart/index.html). These actions will all require a connection between your Python environment and the Giskard Space. Achieve this by initializing a Giskard Client: simply copy the “Create a Giskard Client” snippet diff --git a/docs/hub/spaces-sdks-docker-label-studio.md b/docs/hub/spaces-sdks-docker-label-studio.md index 3719bff1f8..11fe65c3bc 100644 --- a/docs/hub/spaces-sdks-docker-label-studio.md +++ b/docs/hub/spaces-sdks-docker-label-studio.md @@ -43,12 +43,11 @@ local storage for the application database to store configuration, account credentials, and project information. Labeling tasks and data items are also held in local storage. - -Storage in Hugging Face Spaces is ephemeral, and the data you store in the default -configuration can be lost in a reboot or reset of the Space. Because of this, -we strongly encourage you to use the default configuration only for testing and -demonstration purposes. - +> [!WARNING] +> Storage in Hugging Face Spaces is ephemeral, and the data you store in the default +> configuration can be lost in a reboot or reset of the Space. Because of this, +> we strongly encourage you to use the default configuration only for testing and +> demonstration purposes. After launching Label Studio, you will be presented with the standard login screen. You can start by creating a new account using your email address and diff --git a/docs/hub/spaces-sdks-docker-livebook.md b/docs/hub/spaces-sdks-docker-livebook.md index f46c04f23c..7a935864e4 100644 --- a/docs/hub/spaces-sdks-docker-livebook.md +++ b/docs/hub/spaces-sdks-docker-livebook.md @@ -31,11 +31,8 @@ This will start building your Space using Livebook's Docker image. The visibility of the Space must be set to public for the Smart cells feature in Livebook to function properly. However, your Livebook instance will be protected by Livebook authentication. - - -Smart cell is a type of Livebook cell that provides a UI component for accomplishing a specific task. The code for the task is generated automatically based on the user's interactions with the UI, allowing for faster completion of high-level tasks without writing code from scratch. - - +> [!TIP] +> Smart cell is a type of Livebook cell that provides a UI component for accomplishing a specific task. The code for the task is generated automatically based on the user's interactions with the UI, allowing for faster completion of high-level tasks without writing code from scratch. Once the app build is finished, go to the "App" tab in your Space and log in to your Livebook using the password you previously set: diff --git a/docs/hub/spaces-sdks-docker-tabby.md b/docs/hub/spaces-sdks-docker-tabby.md index 30d86a0f30..8e2b02cdf5 100644 --- a/docs/hub/spaces-sdks-docker-tabby.md +++ b/docs/hub/spaces-sdks-docker-tabby.md @@ -24,11 +24,8 @@ You’ll see the *Building status*. Once it becomes *Running*, your Space is rea ![Swagger UI](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/tabby/swagger-ui.png) - - -If you want to customize the title, emojis, and colors of your space, go to "Files and Versions" and edit the metadata of your README.md file. - - +> [!TIP] +> If you want to customize the title, emojis, and colors of your space, go to "Files and Versions" and edit the metadata of your README.md file. ### Your Tabby Space URL diff --git a/docs/hub/spaces-sdks-docker-zenml.md b/docs/hub/spaces-sdks-docker-zenml.md index 6d38e9a1e9..fcdfffa0d7 100644 --- a/docs/hub/spaces-sdks-docker-zenml.md +++ b/docs/hub/spaces-sdks-docker-zenml.md @@ -75,10 +75,9 @@ login to access the dashboard (username: 'default', password: (leave it empty)). Once you have your ZenML server up and running, you can connect to it from your local machine. To do this, you'll need to get your Space's 'Direct URL' (see above). - -Your Space's URL will only be available and usable for connecting from your -local machine if the visibility of the space is set to 'Public'. - +> [!WARNING] +> Your Space's URL will only be available and usable for connecting from your +> local machine if the visibility of the space is set to 'Public'. You can use the 'Direct URL' to connect to your ZenML server from your local machine with the following CLI command (after installing ZenML, and using your custom @@ -91,12 +90,11 @@ zenml connect --url '' --username='default' --passwor You can also use the Direct URL in your browser to use the ZenML dashboard as a fullscreen application (i.e. without the HuggingFace Spaces wrapper around it). - -The ZenML dashboard will currently not work when viewed from within the Huggingface -webpage (i.e. wrapped in the main `https://huggingface.co/...` website). This is on -account of a limitation in how cookies are handled between ZenML and Huggingface. -You **must** view the dashboard from the 'Direct URL' (see above). - +> [!WARNING] +> The ZenML dashboard will currently not work when viewed from within the Huggingface +> webpage (i.e. wrapped in the main `https://huggingface.co/...` website). This is on +> account of a limitation in how cookies are handled between ZenML and Huggingface. +> You **must** view the dashboard from the 'Direct URL' (see above). ## Extra Configuration Options @@ -107,10 +105,9 @@ full details on the various parameters you can change, see [our reference documentation](https://docs.zenml.io/getting-started/deploying-zenml/docker#zenml-server-configuration-options) on configuring ZenML when deployed with Docker. - -If you are using the space just for testing and experimentation, you don't need -to make any changes to the configuration. Everything will work out of the box. - +> [!TIP] +> If you are using the space just for testing and experimentation, you don't need +> to make any changes to the configuration. Everything will work out of the box. You can also use an external secrets backend together with your HuggingFace Spaces as described in [our @@ -120,25 +117,24 @@ configure any secrets you need to use in your`Dockerfile` configuration. [See th documentation](https://huggingface.co/docs/hub/spaces-sdks-docker#secret-management) for more details how to set this up. - -If you wish to use a cloud secrets backend together with ZenML for secrets -management, **you must take the following minimal security precautions** on your ZenML Server on the -Dashboard: - -- change your password on the `default` account that you get when you start. You - can do this from the Dashboard or via the CLI. -- create a new user account with a password and assign it the `admin` role. This - can also be done from the Dashboard (by 'inviting' a new user) or via the CLI. -- reconnect to the server using the new user account and password as described - above, and use this new user account as your working account. - -This is because the default user created by the -HuggingFace Spaces deployment process has no password assigned to it and as the -Space is publicly accessible (since the Space is public) *potentially anyone -could access your secrets without this extra step*. To change your password -navigate to the Settings page by clicking the button in the upper right hand -corner of the Dashboard and then click 'Update Password'. - +> [!WARNING] +> If you wish to use a cloud secrets backend together with ZenML for secrets +> management, **you must take the following minimal security precautions** on your ZenML Server on the +> Dashboard: +> +> - change your password on the `default` account that you get when you start. You +> can do this from the Dashboard or via the CLI. +> - create a new user account with a password and assign it the `admin` role. This +> can also be done from the Dashboard (by 'inviting' a new user) or via the CLI. +> - reconnect to the server using the new user account and password as described +> above, and use this new user account as your working account. +> +> This is because the default user created by the +> HuggingFace Spaces deployment process has no password assigned to it and as the +> Space is publicly accessible (since the Space is public) *potentially anyone +> could access your secrets without this extra step*. To change your password +> navigate to the Settings page by clicking the button in the upper right hand +> corner of the Dashboard and then click 'Update Password'. ## Upgrading your ZenML Server on HF Spaces diff --git a/docs/hub/spaces-sdks-docker.md b/docs/hub/spaces-sdks-docker.md index 52c23cc0b5..49572acb09 100644 --- a/docs/hub/spaces-sdks-docker.md +++ b/docs/hub/spaces-sdks-docker.md @@ -114,9 +114,8 @@ RUN chmod 777 /data ``` You should always avoid superfluous chowns. - -Updating metadata for a file creates a new copy stored in the new layer. Therefore, a recursive chown can result in a very large image due to the duplication of all affected files. - +> [!WARNING] +> Updating metadata for a file creates a new copy stored in the new layer. Therefore, a recursive chown can result in a very large image due to the duplication of all affected files. Rather than fixing permission by running `chown`: ``` diff --git a/docs/hub/spaces-sdks-python.md b/docs/hub/spaces-sdks-python.md index e14b706287..7b0de2f074 100644 --- a/docs/hub/spaces-sdks-python.md +++ b/docs/hub/spaces-sdks-python.md @@ -1,10 +1,7 @@ # Custom Python Spaces - - -Spaces now support arbitrary Dockerfiles so you can host any Python app directly using [Docker Spaces](./spaces-sdks-docker). - - +> [!TIP] +> Spaces now support arbitrary Dockerfiles so you can host any Python app directly using [Docker Spaces](./spaces-sdks-docker). While not an official workflow, you are able to run your own Python + interface stack in Spaces by selecting Gradio as your SDK and serving a frontend on port `7860`. See the [templates](https://huggingface.co/templates#spaces) for examples. diff --git a/docs/hub/spaces-sdks-streamlit.md b/docs/hub/spaces-sdks-streamlit.md index 1d447c69cc..7ac4622130 100644 --- a/docs/hub/spaces-sdks-streamlit.md +++ b/docs/hub/spaces-sdks-streamlit.md @@ -1,13 +1,10 @@ - - -The option to use Streamlit as the default built-in SDK for Spaces is deprecated. -If you wish to deploy a Space with Streamlit, please pick the Docker SDK, then use the Streamlit template. - -
- -
- - +> [!WARNING] +> The option to use Streamlit as the default built-in SDK for Spaces is deprecated. +> If you wish to deploy a Space with Streamlit, please pick the Docker SDK, then use the Streamlit template. +> +>
+> +>
# Streamlit Spaces @@ -26,9 +23,8 @@ You can edit the `sdk_version`, but note that issues may occur when you use an u For in-depth information about Streamlit, refer to the [Streamlit documentation](https://docs.streamlit.io/). - -Only port 8501 is allowed for Streamlit Spaces (default port). As a result if you provide a `config.toml` file for your Space make sure the default port is not overridden. - +> [!WARNING] +> Only port 8501 is allowed for Streamlit Spaces (default port). As a result if you provide a `config.toml` file for your Space make sure the default port is not overridden. ## Your First Streamlit Space: Hot Dog Classifier diff --git a/docs/hub/spaces-storage.md b/docs/hub/spaces-storage.md index 57a8da9f51..294881f6b0 100644 --- a/docs/hub/spaces-storage.md +++ b/docs/hub/spaces-storage.md @@ -25,9 +25,8 @@ Persistent disk space can be upgraded to a larger tier at will, though it cannot If you are using Hugging Face open source libraries, you can make your Space restart faster by setting the environment variable `HF_HOME` to `/data/.huggingface`. Libraries like `transformers`, `diffusers`, `datasets` and others use that environment variable to cache any assets downloaded from the Hugging Face Hub. Setting this variable to the persistent storage path will make sure that cached resources do not need to be re-downloaded when the Space is restarted. - - WARNING: all data stored in the storage is lost when you delete it. - +> [!WARNING] +> WARNING: all data stored in the storage is lost when you delete it. ### Persistent storage specs diff --git a/docs/hub/storage-backends.md b/docs/hub/storage-backends.md index 417902085e..cf09be009f 100644 --- a/docs/hub/storage-backends.md +++ b/docs/hub/storage-backends.md @@ -43,13 +43,10 @@ Unlike Git LFS, which deduplicates at the file level, Xet-enabled repositories d To start using Xet Storage, you need a Xet-enabled repository and a Xet-aware version of the [huggingface_hub](https://huggingface.co/docs/huggingface_hub) Python library. As of May 23rd, 2025, Xet-enabled repositories are the default [for all new users and organizations on the Hub](https://huggingface.co/changelog/xet-default-for-new-users). - - -For user and organization profiles created before May 23rd, 2025, you can make Xet the default for all your repositories by [signing up here](https://huggingface.co/join/xet). You can apply for yourself or your entire organization (requires [admin permissions](https://huggingface.co/docs/hub/organizations-security)). Once approved, all existing repositories will be automatically migrated to Xet and future repositories will be Xet-enabled by default. - -PRO users and Team or Enterprise organizations will be fast-tracked for access. - - +> [!TIP] +> For user and organization profiles created before May 23rd, 2025, you can make Xet the default for all your repositories by [signing up here](https://huggingface.co/join/xet). You can apply for yourself or your entire organization (requires [admin permissions](https://huggingface.co/docs/hub/organizations-security)). Once approved, all existing repositories will be automatically migrated to Xet and future repositories will be Xet-enabled by default. +> +> PRO users and Team or Enterprise organizations will be fast-tracked for access. To access a Xet-aware version of the `huggingface_hub`, simply install the latest version: diff --git a/docs/hub/storage-limits.md b/docs/hub/storage-limits.md index 37c9c60664..dca00de3f6 100644 --- a/docs/hub/storage-limits.md +++ b/docs/hub/storage-limits.md @@ -2,9 +2,8 @@ At Hugging Face our intent is to provide the AI community with as much **free storage space for public repositories** as we can. We do bill for storage space for **private repositories**, above a free tier (see table below). - -Storage limits and policies apply to both model and dataset repositories on the Hub. - +> [!TIP] +> Storage limits and policies apply to both model and dataset repositories on the Hub. We [optimize our infrastructure](https://huggingface.co/blog/xethub-joins-hf) continuously to [scale our storage](https://x.com/julien_c/status/1821540661973160339) for the coming years of growth in AI and Machine learning. diff --git a/docs/hub/storage-regions.md b/docs/hub/storage-regions.md index 8d0cfab843..342cd75658 100644 --- a/docs/hub/storage-regions.md +++ b/docs/hub/storage-regions.md @@ -1,8 +1,7 @@ # Storage Regions on the Hub - -This feature is part of the Team & Enterprise plans. - +> [!WARNING] +> This feature is part of the Team & Enterprise plans. Regions allow you to specify where your organization's models, datasets and Spaces are stored. For non-Enterprise Hub users, repositories are always stored in the US. @@ -39,9 +38,8 @@ This page displays: - An audit of your organization's repository locations - Options to select where new repositories will be stored - -Some advanced compute options for Spaces, such as ZeroGPU, may not be available in all regions. - +> [!TIP] +> Some advanced compute options for Spaces, such as ZeroGPU, may not be available in all regions. ## Repository Tag diff --git a/docs/hub/webhooks-guide-auto-retrain.md b/docs/hub/webhooks-guide-auto-retrain.md index 33565507b5..c21bfcb5b7 100644 --- a/docs/hub/webhooks-guide-auto-retrain.md +++ b/docs/hub/webhooks-guide-auto-retrain.md @@ -1,10 +1,7 @@ # Webhook guide: Setup an automatic system to re-train a model when a dataset changes - - -Webhooks are now publicly available! - - +> [!TIP] +> Webhooks are now publicly available! This guide will help walk you through the setup of an automatic training pipeline on the Hugging Face platform using HF Datasets, Webhooks, Spaces, and AutoTrain. diff --git a/docs/hub/webhooks-guide-discussion-bot.md b/docs/hub/webhooks-guide-discussion-bot.md index b4d0542c33..03e9707d39 100644 --- a/docs/hub/webhooks-guide-discussion-bot.md +++ b/docs/hub/webhooks-guide-discussion-bot.md @@ -1,10 +1,7 @@ # Webhook guide: build a Discussion bot based on BLOOM - - -Webhooks are now publicly available! - - +> [!TIP] +> Webhooks are now publicly available! Here's a short guide on how to use Hugging Face Webhooks to build a bot that replies to Discussion comments on the Hub with a response generated by BLOOM, a multilingual language model, using the free Inference API. @@ -27,9 +24,8 @@ In this guide, we create a separate user account to host a Space and to post com ![discussion-bot-profile](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/webhooks-guides/001-discussion-bot/discussion-bot-profile.png) - - When creating a bot that will interact with other users on the Hub, we ask that you clearly label the account as a "Bot" (see profile screenshot). - +> [!TIP] +> When creating a bot that will interact with other users on the Hub, we ask that you clearly label the account as a "Bot" (see profile screenshot). ## Create a Space that will react to your Webhook diff --git a/docs/hub/webhooks-guide-metadata-review.md b/docs/hub/webhooks-guide-metadata-review.md index ccdf47bfb4..328d8f5852 100644 --- a/docs/hub/webhooks-guide-metadata-review.md +++ b/docs/hub/webhooks-guide-metadata-review.md @@ -1,10 +1,7 @@ # Webhook guide: Setup an automatic metadata quality review for models and datasets - - -Webhooks are now publicly available! - - +> [!TIP] +> Webhooks are now publicly available! This guide will walk you through creating a system that reacts to changes to a user's or organization's models or datasets on the Hub and creates a 'metadata review' for the changed repository. @@ -141,9 +138,8 @@ def create_or_update_report(data): return True ``` - - `:=` is the Python Syntax for an assignment expression operator added to the Python language in version 3.8 (colloquially known as the walrus operator). People have mixed opinions on this syntax, and it doesn't change how Python evaluates the code if you don't use this. You can read more about this operator in this Real Python article. - +> [!TIP] +> `:=` is the Python Syntax for an assignment expression operator added to the Python language in version 3.8 (colloquially known as the walrus operator). People have mixed opinions on this syntax, and it doesn't change how Python evaluates the code if you don't use this. You can read more about this operator in this Real Python article. ## Creating a Webhook to respond to changes on the Hub @@ -168,9 +164,8 @@ This guide creates a separate user account that will post the metadata reviews. ![Bot user account](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/webhooks-guides/003-metadata-review/librarian-bot-profile.png) - - When creating a bot that will interact with other users on the Hub, we ask that you clearly label the account as a "Bot" (see profile screenshot). - +> [!TIP] +> When creating a bot that will interact with other users on the Hub, we ask that you clearly label the account as a "Bot" (see profile screenshot). ## Create a Webhook listener diff --git a/docs/hub/webhooks.md b/docs/hub/webhooks.md index cc1849be45..d126bde44a 100644 --- a/docs/hub/webhooks.md +++ b/docs/hub/webhooks.md @@ -1,10 +1,7 @@ # Webhooks - - -Webhooks are now publicly available! - - +> [!TIP] +> Webhooks are now publicly available! Webhooks are a foundation for MLOps-related features. They allow you to listen for new changes on specific repos or to all repos belonging to particular set of users/organizations (not just your repos, but any repo). @@ -232,11 +229,10 @@ Setting a Webhook secret is useful to make sure payloads sent to your Webhook ha If you set a secret for your Webhook, it will be sent along as an `X-Webhook-Secret` HTTP header on every request. Only ASCII characters are supported. - -It's also possible to add the secret directly in the handler URL. For example, setting it as a query parameter: https://example.com/webhook?secret=XXX. - -This can be helpful if accessing the HTTP headers of the request is complicated for your Webhook handler. - +> [!TIP] +> It's also possible to add the secret directly in the handler URL. For example, setting it as a query parameter: https://example.com/webhook?secret=XXX. +> +> This can be helpful if accessing the HTTP headers of the request is complicated for your Webhook handler. ## Rate limiting