fix eurosat templates
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@ -4,6 +4,8 @@ Below are the class names and templates that are used for collecting the zero-sh
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This file contains prompt data for 26 of the 27 datasets shown in Table 9 of the paper; the text prompts for ImageNet (as well as other [ImageNet Testbed](https://modestyachts.github.io/imagenet-testbed/) datasets in Figure 13) can be found in [this notebook](https://github.com/openai/CLIP/blob/main/notebooks/Prompt_Engineering_for_ImageNet.ipynb), as well as how to ensemble predictions from multiple prompts using these templates.
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If you are viewing this document on GitHub, use the table of contents icon at the upper left to browse the datasets.
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## Birdsnap
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@ -1156,16 +1158,16 @@ templates = [
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```bash
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classes = [
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'AnnualCrop'
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'Forest'
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'HerbaceousVegetation'
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'Highway'
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'Industrial'
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'Pasture'
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'PermanentCrop'
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'Residential'
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'River'
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'SeaLake'
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'forest'
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'permanent crop land'
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'residential buildings or homes or apartments'
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'river'
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'pasture land'
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'lake or sea'
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'brushland or shrubland'
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'annual crop land'
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'industrial buildings or commercial buildings'
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'highway or road'
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],
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templates = [
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