  >
  > ```python
  > # Construction via add_pipe with default GPT3.5 model and NER task
  > config = {"task": {"@llm_tasks": "spacy.NER.v3", "labels": ["PERSON", "ORGANISATION", "LOCATION"]}}
  > llm = nlp.add_pipe("llm")
  >
  > # Construction via add_pipe with task-specific factory and default GPT3.5 model
  > parser = nlp.add_pipe("llm-ner", config=config)
  >
  > # Construction from class
 
</s> remove > # Construction via add_pipe with task-specific factory and default GPT3.5 model
> parser = nlp.add_pipe("llm-ner", config=config)
 </s> add > # Construction via add_pipe with a task-specific factory and default GPT3.5 model
> llm = nlp.add_pipe("llm-ner") </s> remove > # Construction via add_pipe with default GPT3.5 model and NER task
 </s> add > # Construction via add_pipe with the default GPT 3.5 model and an explicitly defined task </s> remove as well as through task-specific component factories:

- `llm_ner`
- `llm_spancat`
- `llm_rel`
- `llm_textcat`
- `llm_sentiment`
- `llm_summarization`
 </s> add as well as through task-specific component factories: `llm_ner`, `llm_spancat`, `llm_rel`,
`llm_textcat`, `llm_sentiment` and `llm_summarization`.
> llm = nlp.add_pipe("llm", config=config)
  >
  > ```python
  > # Construction via add_pipe with default GPT3.5 model and NER task
  > config = {"task": {"@llm_tasks": "spacy.NER.v3", "labels": ["PERSON", "ORGANISATION", "LOCATION"]}}
> llm = nlp.add_pipe("llm", config=config)
  >
  > # Construction via add_pipe with task-specific factory and default GPT3.5 model
  > parser = nlp.add_pipe("llm-ner", config=config)
  >
  > # Construction from class
keep keep keep keep replace keep keep keep keep keep
 Few spacy-llm doc fixes (#12969)

* fix construction example

* shorten task-specific factory list

* small edits to HF models

* small edit to API models

* typo

* fix space

Co-authored-by: Raphael Mitsch <r.mitsch@outlook.com>

---------

Co-authored-by: Raphael Mitsch <r.mitsch@outlook.com> 
website/docs/api/large-language-models.mdx