Spacy-LLM code sample produces no output

Hi,

The code sample below - which is based on an example in Matthew Honnibal's blog "Against LLM maximalism" (https://explosion.ai/blog/against-llm-maximalism) - fails to produce any output. This is surprising given that the pipeline is configured to find the kind of entities present in the sentence being processed.

Note: This is a continuation of Issue #13096 (Spacy-LLM fails with storage not allocated on MPS device).

## How to reproduce the behavior

Here is the code:

```
import spacy

nlp = spacy.blank("en")
nlp.add_pipe("sentencizer")
nlp.add_pipe(
"llm",
config={
"task": {
"@llm_tasks": "spacy.NER.v1",
"labels": "SAAS_PLATFORM,PROGRAMMING_LANGUAGE,OPEN_SOURCE_LIBRARY"
},
"model": {
"@llm_models": "spacy.OpenLLaMA.v1",
"name": "open_llama_3b"
},
},
)

doc = nlp("There's no PyTorch bindings for Go. We just use Microsoft Cognitive Services.")
for ent in doc.ents:
print(ent.text, ent.label_, ent.sent)
```

## Your Environment
Platform: macOS-12.6-arm64-arm-64bit
Python Version: 3.11.4
spaCy Version: 3.6.1