update replicate, clear cuda cache if cuda available

This commit is contained in:
Brett Kuprel 2022-07-04 07:28:44 -04:00
parent 256fd1aab0
commit a21ea6ea14
4 changed files with 13 additions and 13 deletions

12
README.rst vendored
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@ -4,13 +4,13 @@ min(DALL·E)
|Open In Colab|   |Replicate|   |Join us on Discord|
This is a fast, minimal implementation of Boris Daymas `DALL·E
Mini <https://github.com/borisdayma/dalle-mini>`__. It has been stripped
Mega <https://github.com/borisdayma/dalle-mini>`__. It has been stripped
down for inference and converted to PyTorch. The only third party
dependencies are numpy, requests, pillow and torch.
To generate a 3x3 grid of DALL·E Mega images it takes - **35 seconds**
with a P100 in Colab - **15 seconds** with an A100 on Replicate -
**TBD** with an H100 (@NVIDIA?)
It takes - **35 seconds** to generate a 3x3 grid with a P100 in Colab -
**16 seconds** to generate a 4x4 grid with an A100 on Replicate -
**TBD** to generate a 4x4 grid with an H100 (@NVIDIA?)
The flax model and code for converting it to torch can be found
`here <https://github.com/kuprel/min-dalle-flax>`__.
@ -40,7 +40,7 @@ not already there. Once everything has finished initializing, call
.. code:: python
text = 'Dali painting of WallE'
text = 'Dali painting of WALL·E'
image = model.generate_image(text, seed=0, grid_size=4)
display(image)
@ -81,7 +81,7 @@ Use ``image_from_text.py`` to generate images from the command line.
.. code:: bash
$ python image_from_text.py --text='artificial intelligence' --seed=7
$ python image_from_text.py --text='artificial intelligence' --no-mega --seed=7
.. code:: bash

2
cog.yaml vendored
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@ -6,7 +6,7 @@ build:
- "libgl1-mesa-glx"
- "libglib2.0-0"
python_packages:
- "min-dalle==0.2.13"
- "min-dalle==0.2.14"
run:
- pip install torch==1.10.0+cu113 -f https://download.pytorch.org/whl/torch_stable.html

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@ -11,17 +11,17 @@ class Predictor(BasePredictor):
self,
text: str = Input(
description='Text',
default='court sketch of godzilla on trial'
default='Dali painting of WALL·E'
),
seed: int = Input(
description='Seed',
default=6
description='Set the seed to a positive number for reproducible results',
default=-1
),
grid_size: int = Input(
description='Grid Size',
description='Size of the image grid',
ge=1,
le=4,
default=3
default=4
)
) -> Path:
image = self.model.generate_image(text, seed, grid_size=grid_size)

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@ -5,7 +5,7 @@ setuptools.setup(
name='min-dalle',
description = 'min(DALL·E)',
long_description=(Path(__file__).parent / "README.rst").read_text(),
version='0.2.13',
version='0.2.14',
author='Brett Kuprel',
author_email='brkuprel@gmail.com',
url='https://github.com/kuprel/min-dalle',