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