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Colab: Balances the data distribution #1710

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Mar 11, 2024
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Colab: Balances the data distribution #1710

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0be7dd6
colab: balance the use of RAM
Peppe289 Jan 2, 2024
9d1188e
Merge branch 'lllyasviel:main' into main
Peppe289 Jan 13, 2024
11a9d2d
feat: use --always-high-vram by default for Colab, adjust readme
mashb1t Mar 11, 2024
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2 changes: 1 addition & 1 deletion fooocus_colab.ipynb
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Expand Up @@ -12,7 +12,7 @@
"%cd /content\n",
"!git clone https://github.com/lllyasviel/Fooocus.git\n",
"%cd /content/Fooocus\n",
"!python entry_with_update.py --share\n"
"!python entry_with_update.py --share --always-high-vram\n"
]
}
],
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6 changes: 4 additions & 2 deletions readme.md
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Expand Up @@ -115,16 +115,18 @@ See also the common problems and troubleshoots [here](troubleshoot.md).

### Colab

(Last tested - 2023 Dec 12)
(Last tested - 2024 Mar 11)

| Colab | Info
| --- | --- |
[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lllyasviel/Fooocus/blob/main/fooocus_colab.ipynb) | Fooocus Official

In Colab, you can modify the last line to `!python entry_with_update.py --share` or `!python entry_with_update.py --preset anime --share` or `!python entry_with_update.py --preset realistic --share` for Fooocus Default/Anime/Realistic Edition.
In Colab, you can modify the last line to `!python entry_with_update.py --share --always-high-vram` or `!python entry_with_update.py --share --always-high-vram --preset anime` or `!python entry_with_update.py --share --always-high-vram --preset realistic` for Fooocus Default/Anime/Realistic Edition.

Note that this Colab will disable refiner by default because Colab free's resources are relatively limited (and some "big" features like image prompt may cause free-tier Colab to disconnect). We make sure that basic text-to-image is always working on free-tier Colab.

Using `--always-high-vram` shifts resource allocation from RAM to VRAM and achieves the overall best balance between performance, flexibility and stability on the default T4 instance.

Thanks to [camenduru](https://github.com/camenduru)!

### Linux (Using Anaconda)
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