Spaces:
Running
Running
update duration for zero gpu
Browse files
app.py
CHANGED
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@@ -191,7 +191,11 @@ ALWAYS use ZeroGPU for GPU-dependent functions in Gradio apps:
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1. Import the spaces module: `import spaces`
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2. Decorate GPU-dependent functions with `@spaces.GPU`
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Example usage:
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```python
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@@ -201,7 +205,7 @@ from diffusers import DiffusionPipeline
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pipe = DiffusionPipeline.from_pretrained(...)
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pipe.to('cuda')
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@spaces.GPU
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def generate(prompt):
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return pipe(prompt).images
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@@ -212,6 +216,14 @@ gr.Interface(
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).launch()
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```
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Functions that typically need @spaces.GPU:
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- Image generation (text-to-image, image-to-image)
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- Video generation
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@@ -234,7 +246,11 @@ ALWAYS use ZeroGPU for GPU-dependent functions in Gradio apps:
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1. Import the spaces module: `import spaces`
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2. Decorate GPU-dependent functions with `@spaces.GPU`
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-
3.
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Example usage:
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```python
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@@ -244,7 +260,7 @@ from diffusers import DiffusionPipeline
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pipe = DiffusionPipeline.from_pretrained(...)
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pipe.to('cuda')
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-
@spaces.GPU
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def generate(prompt):
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return pipe(prompt).images
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@@ -255,6 +271,14 @@ gr.Interface(
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).launch()
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```
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Functions that typically need @spaces.GPU:
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- Image generation (text-to-image, image-to-image)
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- Video generation
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1. Import the spaces module: `import spaces`
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2. Decorate GPU-dependent functions with `@spaces.GPU`
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3. Specify appropriate duration based on expected runtime:
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- Quick inference (< 30s): `@spaces.GPU(duration=30)`
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- Standard generation (30-60s): `@spaces.GPU` (default 60s)
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- Complex generation (60-120s): `@spaces.GPU(duration=120)`
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- Heavy processing (120-180s): `@spaces.GPU(duration=180)`
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Example usage:
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```python
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pipe = DiffusionPipeline.from_pretrained(...)
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pipe.to('cuda')
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@spaces.GPU(duration=120)
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def generate(prompt):
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return pipe(prompt).images
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).launch()
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```
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Duration Guidelines:
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- Shorter durations improve queue priority for users
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- Text-to-image: typically 30-60 seconds
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- Image-to-image: typically 20-40 seconds
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- Video generation: typically 60-180 seconds
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- Audio/music generation: typically 30-90 seconds
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- Model loading + inference: add 10-30s buffer
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Functions that typically need @spaces.GPU:
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- Image generation (text-to-image, image-to-image)
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- Video generation
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1. Import the spaces module: `import spaces`
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2. Decorate GPU-dependent functions with `@spaces.GPU`
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+
3. Specify appropriate duration based on expected runtime:
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+
- Quick inference (< 30s): `@spaces.GPU(duration=30)`
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+
- Standard generation (30-60s): `@spaces.GPU` (default 60s)
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+
- Complex generation (60-120s): `@spaces.GPU(duration=120)`
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- Heavy processing (120-180s): `@spaces.GPU(duration=180)`
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Example usage:
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```python
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pipe = DiffusionPipeline.from_pretrained(...)
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pipe.to('cuda')
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@spaces.GPU(duration=120)
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def generate(prompt):
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return pipe(prompt).images
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).launch()
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```
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+
Duration Guidelines:
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- Shorter durations improve queue priority for users
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- Text-to-image: typically 30-60 seconds
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+
- Image-to-image: typically 20-40 seconds
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+
- Video generation: typically 60-180 seconds
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- Audio/music generation: typically 30-90 seconds
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- Model loading + inference: add 10-30s buffer
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+
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Functions that typically need @spaces.GPU:
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- Image generation (text-to-image, image-to-image)
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- Video generation
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