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Raphael Mitsch 2023-11-29 10:11:57 +01:00
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14
website/docs/api/large-language-models.mdx
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@ -357,13 +357,13 @@ candidate.
> path = ${paths.el_kb} > path = ${paths.el_kb}
> ``` > ```
| Argument | Description | | Argument | Description |
| --------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | --------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `template` | Custom prompt template to send to LLM model. Defaults to [entity_linker.v1.jinja](https://github.com/explosion/spacy-llm/blob/main/spacy_llm/tasks/templates/entity_linker.v1.jinja). ~~str~~ | | `template` | Custom prompt template to send to LLM model. Defaults to [entity_linker.v1.jinja](https://github.com/explosion/spacy-llm/blob/main/spacy_llm/tasks/templates/entity_linker.v1.jinja). ~~str~~ |
| `parse_responses` | Callable for parsing LLM responses for this task. Defaults to the internal parsing method for this task. ~~Optional[TaskResponseParser[EntityLinkerTask]]~~ | | `parse_responses` | Callable for parsing LLM responses for this task. Defaults to the internal parsing method for this task. ~~Optional[TaskResponseParser[EntityLinkerTask]]~~ |
| `prompt_example_type` | Type to use for fewshot examples. Defaults to `ELExample`. ~~Optional[Type[FewshotExample]]~~ | | `prompt_example_type` | Type to use for fewshot examples. Defaults to `ELExample`. ~~Optional[Type[FewshotExample]]~~ |
| `examples` | Optional callable that reads a file containing task examples for few-shot learning. If `None` is passed, zero-shot learning will be used. Defaults to `None`. ~~ExamplesConfigType~~ | | `examples` | Optional callable that reads a file containing task examples for few-shot learning. If `None` is passed, zero-shot learning will be used. Defaults to `None`. ~~ExamplesConfigType~~ |
| `scorer` | Scorer function. Defaults to the metric used by spaCy to evaluate entity linking performance. ~~Optional[Scorer]~~ | | `scorer` | Scorer function. Defaults to the metric used by spaCy to evaluate entity linking performance. ~~Optional[Scorer]~~ |
##### spacy.CandidateSelector.v1 {id="candidate-selector-v1"} ##### spacy.CandidateSelector.v1 {id="candidate-selector-v1"}

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website/docs/usage/large-language-models.mdx
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@ -357,7 +357,7 @@ evaluate the component.
| Component | Description | | Component | Description |
| ----------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------- | | ----------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------- |
| [`spacy.EntityLinker.v1`](/api/large-language-models#el-v1) | The entity linking task prompts the model to link all entities in a given text to entries in a knowledge base. | | [`spacy.EntityLinker.v1`](/api/large-language-models#el-v1) | The entity linking task prompts the model to link all entities in a given text to entries in a knowledge base. |
| [`spacy.Summarization.v1`](/api/large-language-models#summarization-v1) | The summarization task prompts the model for a concise summary of the provided text. | | [`spacy.Summarization.v1`](/api/large-language-models#summarization-v1) | The summarization task prompts the model for a concise summary of the provided text. |
| [`spacy.NER.v3`](/api/large-language-models#ner-v3) | Implements Chain-of-Thought reasoning for NER extraction - obtains higher accuracy than v1 or v2. | | [`spacy.NER.v3`](/api/large-language-models#ner-v3) | Implements Chain-of-Thought reasoning for NER extraction - obtains higher accuracy than v1 or v2. |
| [`spacy.NER.v2`](/api/large-language-models#ner-v2) | Builds on v1 and additionally supports defining the provided labels with explicit descriptions. | | [`spacy.NER.v2`](/api/large-language-models#ner-v2) | Builds on v1 and additionally supports defining the provided labels with explicit descriptions. |