huggingface · julien-c · Oct 29, 2024 · Oct 28, 2024 · Oct 28, 2024 · Oct 28, 2024
diff --git a/docs/hub/_toctree.yml b/docs/hub/_toctree.yml
@@ -331,11 +331,13 @@
       - local: storage-regions
         title: Storage Regions
       - local: enterprise-hub-datasets
-        title: Dataset viewer for Private datasets
+        title: Private datasets viewer
       - local: enterprise-hub-resource-groups
-        title: Resource Groups (Advanced Access Control)
+        title: Resource Groups (Access Control)
       - local: advanced-compute-options
         title: Advanced Compute Options
+      - local: enterprise-hub-advanced-security
+        title: Advanced Security
       - local: enterprise-hub-tokens-management
         title: Tokens Management
       - local: enterprise-hub-analytics

diff --git a/docs/hub/advanced-compute-options.md b/docs/hub/advanced-compute-options.md
@@ -6,6 +6,19 @@ Enterprise Hub organizations gain access to advanced compute options to accelera
 This feature is part of the <a href="https://huggingface.co/enterprise" target="_blank">Enterprise Hub</a>.
 </Tip>
 
+## Host ZeroGPU Spaces in your organization
+
+ZeroGPU is a dynamic GPU allocation system that optimizes AI deployment on Hugging Face Spaces. By automatically allocating and releasing NVIDIA A100 GPUs (40GB VRAM) as needed, organizations can efficiently serve their AI applications without dedicated GPU instances.
+
+**Key benefits for organizations**
+
+- **Free GPU Access**: Access powerful NVIDIA A100 GPUs at no additional cost through dynamic allocation
+- **Enhanced Resource Management**: Host up to 50 ZeroGPU Spaces for efficient team-wide AI deployment
+- **Simplified Deployment**: Easy integration with PyTorch-based models and Hugging Face libraries
+- **Enterprise-Grade Infrastructure**: Access to high-performance NVIDIA A100 GPUs with 40GB VRAM per workload
+
+[Learn more about ZeroGPU →](https://huggingface.co/docs/hub/spaces-zerogpu)
+
 ## Train on NVIDIA DGX Cloud
 
 Train on NVIDIA DGX Cloud offers a simple no-code training job creation experience powered by Hugging Face AutoTrain and Hugging Face Spaces. Instantly access NVIDIA GPUs and avoid the time-consuming work of writing, testing, and debugging training scripts for AI models.
@@ -18,30 +31,30 @@ Read the [blogpost for Train on NVIDIA DGX Cloud](https://huggingface.co/blog/tr
 
 #### Transformers
 
-| Architecture              |
-|---------------------------|
-| Llama                     |
-| Falcon                    |
-| Mistral                   |
-| Mixtral                   | 
-| T5                        |
-| gemma                     |
+| Architecture |
+| ------------ |
+| Llama        |
+| Falcon       |
+| Mistral      |
+| Mixtral      |
+| T5           |
+| gemma        |
 
 #### Diffusers
 
-| Architecture              |
-|---------------------------|
-| Stable Diffusion          |
-| Stable Diffusion XL       |
+| Architecture        |
+| ------------------- |
+| Stable Diffusion    |
+| Stable Diffusion XL |
 
 ### Pricing
 
 Usage of Train on NVIDIA DGX Cloud is billed by the minute of the GPU instances used during your training jobs. Usage fees accrue to your Enterprise Hub Organizations’ current monthly billing cycle, once a job is completed. You can check your current and past usage at any time within the billing settings of your Enterprise Hub Organization.
 
-| NVIDIA GPU                | GPU Memory                | On-Demand Price/hr        |
-|---------------------------|---------------------------|---------------------------|
-| NVIDIA L40S               | 48GB                      |$2.75                      |
-| NVIDIA H100               | 80GB                      |$8.25                      |
+| NVIDIA GPU  | GPU Memory | On-Demand Price/hr |
+| ----------- | ---------- | ------------------ |
+| NVIDIA L40S | 48GB       | $2.75              |
+| NVIDIA H100 | 80GB       | $8.25              |
 
 ## NVIDIA NIM API (serverless)
 
@@ -59,8 +72,8 @@ You can find all supported models in [this NVIDIA Collection](https://huggingfac
 
 Usage of NVIDIA NIM API (serverless) is billed based on the compute time spent per request. Usage fees accrue to your Enterprise Hub Organizations’ current monthly billing cycle, once a job is completed. You can check your current and past usage at any time within the billing settings of your Enterprise Hub Organization.
 
-| NVIDIA GPU                | GPU Memory                | On-Demand Price/hr        |
-|---------------------------|---------------------------|---------------------------|
-| NVIDIA H100               | 80GB                      |$8.25                      |
+| NVIDIA GPU  | GPU Memory | On-Demand Price/hr |
+| ----------- | ---------- | ------------------ |
+| NVIDIA H100 | 80GB       | $8.25              |
 
-The total cost for a request will depend on the model size, the number of GPUs required, and the time taken to process the request. For each model, you can find which hardware configuration is used in the notes of [this NVIDIA Collection](https://huggingface.co/collections/nvidia/nim-66a3c6fcdcb5bbc6e975b508).
+The total cost for a request will depend on the model size, the number of GPUs required, and the time taken to process the request. For each model, you can find which hardware configuration is used in the notes of [this NVIDIA Collection](https://huggingface.co/collections/nvidia/nim-66a3c6fcdcb5bbc6e975b508).
diff --git a/docs/hub/audit-logs.md b/docs/hub/audit-logs.md
@@ -6,6 +6,76 @@ This feature is part of the <a href="https://huggingface.co/enterprise" target="
 
 Audit Logs enable organization admins to easily review actions taken by members, including organization membership, repository settings and billing changes.
 
-Audit Logs are accessible through your organization admin settings.
+![](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/enterprise/audit-logs.png)
 
-![](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/storage-regions/audit-logs.png)
+## Accessing Audit Logs
+
+Audit Logs are accessible through your organization settings. Each log entry includes:
+
+- Who performed the action
+- What type of action was taken
+- A description of the change
+- Location and anonymized IP address
+- Date and time of the action
+
+You can also download the complete audit log as a JSON file for further analysis.
+
+## What Events Are Tracked?
+
+### Organization Management & Security
+
+- Core organization changes
+  - Creation, deletion, and restoration
+  - Name changes and settings updates
+- Security management
+  - Security token rotation
+  - Token approval system (enabling/disabling, authorization requests, approvals, denials, revocations)
+  - SSO events (logins and joins)
+
+### Membership and Access Control
+
+- Member lifecycle
+  - Invitations (sending, accepting) and automatic joins
+  - Adding and removing members
+  - Role changes and departures
+- Join settings
+  - Domain-based access
+  - Automatic join configurations
+
+### Content and Resource Management
+
+- Repository administration
+  - Core actions (creation, deletion, moving, duplication)
+  - Settings and configuration changes
+  - Enabling/disabling repositories
+  - DOI management
+  - Resource group assignments
+- Collections
+  - Creation and deletion events
+- Repository security
+  - Secrets management (individual and bulk)
+  - Variables handling (individual and bulk)
+- Spaces configuration
+  - Storage modifications
+  - Hardware settings
+  - Sleep time adjustments
+
+### Billing and AWS Integration
+
+- Payment management
+  - Payment methods (adding/removing)
+  - Customer account creation
+  - AWS integration setup and removal
+- Subscription lifecycle
+  - Starting and renewing
+  - Updates and cancellations
+  - Cancellation reversals
+
+### Resource Groups
+
+- Administrative actions
+  - Creation and deletion
+  - Settings modifications
+- Member management
+  - Adding and removing users
+  - Role assignments and changes
diff --git a/docs/hub/enterprise-hub-advanced-security.md b/docs/hub/enterprise-hub-advanced-security.md
@@ -0,0 +1,29 @@
+# Advanced Security
+
+<Tip warning={true}>
+This feature is part of the <a href="https://huggingface.co/enterprise" target="_blank">Enterprise Hub</a>.
+</Tip>
+
+Enterprise Hub organizations can improve their security with advanced security controls for both members and repositories.
+
+<div class="flex justify-center">
+    <img class="block dark:hidden !m-0" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/enterprise/advanced-security.png" alt="screenshot of the Dataset Viewer on a private dataset owned by an Enterprise Hub organization."/>
+    <img class="hidden dark:block !m-0" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/enterprise/advanced-security-dark.png" alt="screenshot of the Dataset Viewer on a private dataset owned by an Enterprise Hub organization."/>
+</div>
+
+## Members Security
+
+Configure additional security settings to protect your organization:
+
+- **Two-Factor Authentication (2FA)**: Require all organization members to enable 2FA for enhanced account security.
+- **User Approval**: For organizations with a verified domain name, require admin approval for new users with matching email addresses. This adds a verified badge to your organization page.
+
+## Repository Visibility Controls
+
+Manage the default visibility of repositories in your organization:
+
+- **Public by default**: New repositories are created with public visibility
+- **Private by default**: New repositories are created with private visibility. Note that changing this setting will not affect existing repositories.
+- **Private only**: Enforce private visibility for all new repositories, with only organization admins able to change visibility settings
+
+These settings help organizations maintain control of their ownership while enabling collaboration when needed.
diff --git a/docs/hub/enterprise-hub.md b/docs/hub/enterprise-hub.md
@@ -2,15 +2,16 @@
 
 Enterprise Hub adds advanced capabilities to organizations, enabling safe, compliant and managed collaboration for companies and teams on Hugging Face.
 
-![](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/storage-regions/enterprise-hub.png)
+![](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/enterprise/enterprise-hub.png)
 
 In this section we will document the following Enterprise Hub features:
 
 - [SSO](./enterprise-sso)
 - [Audit Logs](./audit-logs)
 - [Storage Regions](./storage-regions)
-- [Dataset viewer for Private datasets](./enterprise-hub-datasets)
+- [Private datasets viewer](./enterprise-hub-datasets)
 - [Resource Groups](./security-resource-groups)
 - [Advanced Compute Options](./advanced-compute-options)
+- [Advanced Security](./enterprise-hub-advanced-security)
 - [Tokens Management](./enterprise-hub-tokens-management)
 - [Analytics](./enterprise-hub-analytics)
diff --git a/docs/hub/organizations.md b/docs/hub/organizations.md
@@ -10,8 +10,12 @@ If an organization needs to track user access to a dataset due to licensing or p
 - [Organization Cards](./organizations-cards)
 - [Access Control in Organizations](./organizations-security)
 - [Enterprise Hub features](./enterprise-hub)
-  - [SSO in Organizations](./enterprise-sso)
+  - [SSO](./enterprise-sso)
   - [Audit Logs](./audit-logs)
   - [Storage Regions](./storage-regions)
-  - [Dataset viewer for Private datasets](./enterprise-hub-datasets)
+  - [Private datasets viewer](./enterprise-hub-datasets)
   - [Resource Groups](./security-resource-groups)
+  - [Advanced Compute Options](./advanced-compute-options)
+  - [Advanced Security](./enterprise-hub-advanced-security)
+  - [Tokens Management](./enterprise-hub-tokens-management)
+  - [Analytics](./enterprise-hub-analytics)
diff --git a/docs/hub/storage-regions.md b/docs/hub/storage-regions.md
@@ -1,53 +1,53 @@
 # Storage Regions on the Hub
 
-Regions let you decide where your org's models and datasets will be stored.
+Regions allow you to specify where your organization's models and datasets are stored.
 
 <Tip warning={true}>
 This feature is part of the <a href="https://huggingface.co/enterprise" target="_blank">Enterprise Hub</a>.
 </Tip>
 
-This has two main benefits:
+This offers two key benefits:
 
 - Regulatory and legal compliance
-- Performance (improved download and upload speeds and latency)
+- Performance (faster download/upload speeds and lower latency)
 
-Currently we support the following regions:
+Currently available regions:
 
 - US 🇺🇸
 - EU 🇪🇺
-- coming soon: Asia-Pacific 🌏
+- Coming soon: Asia-Pacific 🌏
 
 ## How to set up
 
-If your organization is subscribed to Enterprise Hub, you will be able to see the Regions settings page:
+Organizations subscribed to Enterprise Hub can access the Regions settings page:
 
 ![](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/storage-regions/feature-annotated.png)
 
-On that page you can see:
+This page displays:
 
-- an audit of where your organization repos are currently located
-- dropdowns to select where your repos will be created
+- An audit of your organization's repository locations
+- Options to select where new repositories will be stored
 
 ## Repository Tag
 
-Any repo (model or dataset) stored in a non-default location will display its Region directly as a tag. That way your organization's members can see at a glance where repos are located.
+Any repository (model or dataset) stored in a non-default location displays its Region as a tag, allowing organization members to quickly identify repository locations.
 
 <div class="flex justify-center">
 <img class="block" width="400" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/storage-regions/tag-on-repo.png"/>
 </div>
 
 ## Regulatory and legal compliance
 
-In regulated industries, companies may be required to store data in a specific region.
+Regulated industries often require data storage in specific regions.
 
-For companies in the EU, that means you can use the Hub to build ML in a GDPR compliant way: with datasets, models and inference endpoints all stored within EU data centers.
+For EU companies, you can use the Hub for ML development in a GDPR-compliant manner, with datasets, models and inference endpoints stored in EU data centers.
 
 ## Performance
 
-Storing your models or your datasets closer to your team and infrastructure also means significantly improved performance, for both uploads and downloads.
+Storing models and datasets closer to your team and infrastructure significantly improves performance for both uploads and downloads.
 
-This makes a big difference considering model weights and dataset files are usually very large.
+This impact is substantial given the typically large size of model weights and dataset files.
 
 ![](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/storage-regions/upload-speed.png)
 
-As an example, if you are located in Europe and store your repositories in the EU region, you can expect to see ~4-5x faster upload and download speeds vs. if they were stored in the US.
+For example, European users storing repositories in the EU region can expect approximately 4-5x faster upload and download speeds compared to US storage.