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fix typo in links

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svlandeg 2023-09-01 11:53:41 +02:00
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website/docs/api/large-language-models.mdx
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@ -120,7 +120,7 @@ note that this requirement will be included in the prompt, but the task doesn't
perform a hard cut-off. It's hence possible that your summary exceeds
`max_n_words`.
To perform [few-shot learning](/usage/large-langauge-models#few-shot-prompts),
To perform [few-shot learning](/usage/large-language-models#few-shot-prompts),
you can write down a few examples in a separate file, and provide these to be
injected into the prompt to the LLM. The default reader `spacy.FewShotReader.v1`
supports `.yml`, `.yaml`, `.json` and `.jsonl`.
@ -249,7 +249,7 @@ the following parameters:
span to the next token boundaries, e.g. expanding `"New Y"` out to
`"New York"`.
To perform [few-shot learning](/usage/large-langauge-models#few-shot-prompts),
To perform [few-shot learning](/usage/large-language-models#few-shot-prompts),
you can write down a few examples in a separate file, and provide these to be
injected into the prompt to the LLM. The default reader `spacy.FewShotReader.v1`
supports `.yml`, `.yaml`, `.json` and `.jsonl`.
@ -423,7 +423,7 @@ prompting.
| `allow_none` | When set to `True`, allows the LLM to not return any of the given label. The resulting dict in `doc.cats` will have `0.0` scores for all labels. Deafults to `True`. ~~bool~~ |
| `verbose` | If set to `True`, warnings will be generated when the LLM returns invalid responses. Deafults to `False`. ~~bool~~ |
To perform [few-shot learning](/usage/large-langauge-models#few-shot-prompts),
To perform [few-shot learning](/usage/large-language-models#few-shot-prompts),
you can write down a few examples in a separate file, and provide these to be
injected into the prompt to the LLM. The default reader `spacy.FewShotReader.v1`
supports `.yml`, `.yaml`, `.json` and `.jsonl`.
@ -473,7 +473,7 @@ on an upstream NER component for entities extraction.
| `normalizer` | Function that normalizes the labels as returned by the LLM. If `None`, falls back to `spacy.LowercaseNormalizer.v1`. Defaults to `None`. ~~Optional[Callable[[str], str]]~~ |
| `verbose` | If set to `True`, warnings will be generated when the LLM returns invalid responses. Defaults to `False`. ~~bool~~ |
To perform [few-shot learning](/usage/large-langauge-models#few-shot-prompts),
To perform [few-shot learning](/usage/large-language-models#few-shot-prompts),
you can write down a few examples in a separate file, and provide these to be
injected into the prompt to the LLM. The default reader `spacy.FewShotReader.v1`
supports `.yml`, `.yaml`, `.json` and `.jsonl`.
@ -539,7 +539,7 @@ doesn't match the number of tokens from the pipeline's tokenizer, no lemmas are
stored in the corresponding doc's tokens. Otherwise the tokens `.lemma_`
property is updated with the lemma suggested by the LLM.
To perform [few-shot learning](/usage/large-langauge-models#few-shot-prompts),
To perform [few-shot learning](/usage/large-language-models#few-shot-prompts),
you can write down a few examples in a separate file, and provide these to be
injected into the prompt to the LLM. The default reader `spacy.FewShotReader.v1`
supports `.yml`, `.yaml`, `.json` and `.jsonl`.
@ -596,7 +596,7 @@ This task supports both zero-shot and few-shot prompting.
| `examples` | Optional function that generates examples for few-shot learning. Defaults to `None`. ~~Optional[Callable[[], Iterable[Any]]]~~ |
| `field` | Name of extension attribute to store summary in (i. e. the summary will be available in `doc._.{field}`). Defaults to `sentiment`. ~~str~~ |
To perform [few-shot learning](/usage/large-langauge-models#few-shot-prompts),
To perform [few-shot learning](/usage/large-language-models#few-shot-prompts),
you can write down a few examples in a separate file, and provide these to be
injected into the prompt to the LLM. The default reader `spacy.FewShotReader.v1`
supports `.yml`, `.yaml`, `.json` and `.jsonl`.