Spaces:
Running
Running
title: README | |
emoji: π | |
colorFrom: indigo | |
colorTo: indigo | |
sdk: static | |
pinned: false | |
# ZeroGPU Spaces | |
<div style="background-color: rgba(255, 255, 255, 0.3);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="https://huggingface.co/subscribe/pro">PRO subscribers</a>. | |
</div> | |
<div style="background-color: rgba(255, 255, 255, 0.3);color: rgb(0 0 0);border-radius: 8px;padding: 0.5rem 1rem; margin-top: 10px;"> | |
<span style="font-weight: 600;">Please share your feedback about ZeroGPU</span> in the <a href="https://huggingface.co/spaces/zero-gpu-explorers/README/discussions">Community tab</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. β We should accept you shortly after checking your HF profile | |