add doc

Author: gary149

docs/hub/_toctree.yml

@@ -238,6 +238,8 @@
       title: Using Spaces for Organization Cards
   - local: spaces-gpus
     title: Spaces GPU Upgrades
+  - local: spaces-zerogpu
+    title: Spaces ZeroGPU
   - local: spaces-storage
     title: Spaces Persistent Storage
   - local: spaces-sdks-gradio

docs/hub/spaces-zerogpu.md

@@ -0,0 +1,93 @@
+# Spaces ZeroGPU: Dynamic GPU Allocation for Spaces
+
+<img src="https://cdn-uploads.huggingface.co/production/uploads/5f17f0a0925b9863e28ad517/naVZI-v41zNxmGlhEhGDJ.gif" style="max-width: 550px; width: 100%" alt="ZeroGPU schema" />
+
+ZeroGPU introduces a new approach to GPU utilization in Hugging Face Spaces. This innovative hardware solution offers two primary benefits:
+
+1. **Free GPU Access**: Enables cost-effective GPU usage for Spaces.
+2. **Multi-GPU Support**: Allows Spaces to leverage multiple GPUs concurrently on a single applications.
+
+ZeroGPU achieves these goals by implementing an efficient GPU allocation system, dynamically assigning and releasing GPUs as needed. This contrasts with traditional GPU Spaces, which are limited to a single dedicated GPU.
+
+## Using and hosting ZeroGPU Spaces
+
+- **Using existing ZeroGPU Spaces**
+  - ZeroGPU Spaces are available to use for free to all users. (Visit [the curated list](https://huggingface.co/spaces/enzostvs/zero-gpu-spaces)).
+  - [PRO users](https://huggingface.co/subscribe/pro) get x5 more daily usage quota and highest priority in GPU queues when using any ZeroGPU Spaces.
+- **Hosting your own ZeroGPU Spaces**
+  - Personal accounts: [Subscribe to PRO](https://huggingface.co/settings/billing/subscription) to access ZeroGPU in the hardware options when creating a new Gradio SDK Space.
+  - Organizations: [Subscribe to the Enterprise Hub](https://huggingface.co/enterprise) to enable ZeroGPU Spaces for all organization members.
+
+## Technical Specifications
+
+- **GPU Type**: Nvidia A100
+- **Available VRAM**: 40GB per workload
+
+## Compatibility
+
+ZeroGPU Spaces are designed to be compatible with most PyTorch-based GPU Spaces. While compatibility is enhanced for high-level Hugging Face libraries like `transformers` and `diffusers`, users should be aware that:
+
+- Currently, ZeroGPU Spaces are exclusively compatible with the **Gradio SDK**.
+- ZeroGPU Spaces may have limited compatibility compared to standard GPU Spaces.
+- Unexpected issues may arise in some scenarios.
+
+### Supported Versions
+
+- Gradio: 4+
+- PyTorch: 2.0.1, 2.1.2, 2.2.2, 2.4.0 (Note: 2.3.x is not supported due to a [PyTorch bug](https://github.com/pytorch/pytorch/issues/122085))
+- Python: 3.10.13
+
+## Getting started with ZeroGPU
+
+To utilize ZeroGPU in your Space, follow these steps:
+
+1. Make sure the ZeroGPU hardware is selected in your Space settings.
+2. Import the `spaces` module.
+3. Decorate GPU-dependent functions with `@spaces.GPU`.
+
+This decoration process allows the Space to request a GPU when the function is called and release it upon completion.
+
+### Example Usage
+
+```python
+import spaces
+from diffusers import DiffusionPipeline
+
+pipe = DiffusionPipeline.from_pretrained(...)
+pipe.to('cuda')
+
+@spaces.GPU
+def generate(prompt):
+    return pipe(prompt).images
+
+gr.Interface(
+    fn=generate,
+    inputs=gr.Text(),
+    outputs=gr.Gallery(),
+).launch()
+```
+
+Note: The `@spaces.GPU` decorator is designed to be effect-free in non-ZeroGPU environments, ensuring compatibility across different setups.
+
+## Duration Management
+
+For functions expected to exceed the default 60-second runtime, specify a custom duration:
+
+```python
+@spaces.GPU(duration=120)
+def generate(prompt):
+   return pipe(prompt).images
+```
+
+This sets the maximum function runtime to 120 seconds. Specifying shorter durations for quicker functions can improve queue priority for Space visitors.
+
+## Limitations
+
+- **Personal accounts (PRO subscribers)**: Maximum of 10 ZeroGPU Spaces.
+- **Organization accounts (Enterprise Hub)**: Maximum of 50 ZeroGPU Spaces.
+
+By leveraging ZeroGPU, developers can create more efficient and scalable Spaces, maximizing GPU utilization while minimizing costs.
+
+## Feedback
+
+You can share your feedback on Spaces ZeroGPU directly on the HF Hub: https://huggingface.co/spaces/zero-gpu-explorers/README/discussions