Update README.md

README.md

@@ -7,4 +7,49 @@ sdk: static
 pinned: false
 ---
 
-# ZeroGPU Explorers
+# ZeroGPU Spaces
+
+*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)
+
+
+# Compatibility
+
+*ZeroGPU* Spaces should mostly be compatible with any PyTorch-based GPU Space.<br>
+Compatibilty 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 work with the **Gradio SDK**
+
+# 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