Spaces:
Running
Running
| title: README | |
| emoji: 🌍 | |
| colorFrom: indigo | |
| colorTo: indigo | |
| sdk: static | |
| pinned: false | |
| # ZeroGPU Spaces | |
| <div style="background-color: rgb(224 224 224);color: rgb(0 0 0);border-radius: 8px;padding: 0.5rem 1rem;"> | |
| <span style="font-weight: 600;">ZeroGPU is currently in beta.</span> It's available in early access for <a href="/subscribe/pro">PRO subscribers</a>. | |
| </div> | |
| <img src="https://cdn-uploads.huggingface.co/production/uploads/5f17f0a0925b9863e28ad517/cAlvAOu9QC547zrmRVpS5.gif" style="width:100%;"/> | |
| *ZeroGPU* is a new kind of hardware for Spaces. | |
| It has two goals : | |
| - Provide **free GPU access** for Spaces | |
| - Allow Spaces to run on **multiple GPUs** | |
| This is achieved by making Spaces efficiently hold and release GPUs as needed | |
| (as opposed to a classical GPU Space that holds exactly one GPU at any point in time) | |
| ZeroGPU uses _Nvidia A100_ GPU devices under the hood (40GB of vRAM are available for each workloads) | |
| <img src="https://cdn-uploads.huggingface.co/production/uploads/5f17f0a0925b9863e28ad517/naVZI-v41zNxmGlhEhGDJ.gif" style="width: 100%; max-width:550px"/> | |
| # Compatibility | |
| *ZeroGPU* Spaces should mostly be compatible with any PyTorch-based GPU Space.<br> | |
| Compatibility with high level HF libraries like `transformers` or `diffusers` is slightly more guaranteed<br> | |
| That said, ZeroGPU Spaces are not as broadly compatible as classical GPU Spaces and you might still encounter unexpected bugs | |
| Also, for now, ZeroGPU Spaces only works with the **Gradio SDK** | |
| Supported versions: | |
| - Gradio: 4+ | |
| - PyTorch: All versions from `2.0.0` to `2.2.0` | |
| - Python: `3.10.13` | |
| # Usage | |
| In order to make your Space work with ZeroGPU you need to **decorate** the Python functions that actually require a GPU with `@spaces.GPU`<br> | |
| During the time when a decorated function is invoked, the Space will be attributed a GPU, and it will release it upon completion of the function.<br> | |
| Here is a practical example : | |
| ```diff | |
| +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() | |
| ``` | |
| 1. We first `import spaces` (importing it first might prevent some issues but is not mandatory) | |
| 2. Then we decorate the `generate` function by adding a `@spaces.GPU` line before its definition | |
| Note that `@spaces.GPU` is effect-free and can be safely used on non-ZeroGPU environments | |
| ## Duration | |
| If you expect your GPU function to take more than __60s__ then you need to specify a `duration` param in the decorator like: | |
| ```python | |
| @spaces.GPU(duration=120) | |
| def generate(prompt): | |
| return pipe(prompt).images | |
| ``` | |
| It will set the maximum duration of your function call to 120s. | |
| You can also specify a duration if you know that your function will take far less than the 60s default. | |
| The lower the duration, the higher priority your Space visitors will have in the queue | |
| # Early access | |
| Feel free to join this organization if you want to try ZeroGPU as a Space author. ✋ We should accept you shortly after checking your HF profile | |