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Rephrase.

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Raphael Mitsch 2023-10-11 12:16:40 +02:00
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website/docs/api/large-language-models.mdx
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@ -754,8 +754,9 @@ path = "textcat_examples.json"
If you want to perform few-shot learning with a binary classifier (i. e. a text
either should or should not be assigned to a given class), you can provide
positive and negative examples with the POS/NEG label. An example for spam
classification:
positive and negative examples with answers of "POS" or "NEG". "POS" means that
this example should be assigned the class label defined in the configuration,
"NEG" means it shouldn't. E. g. for spam classification:
```json
[