Running the first example we get a different score

[benhealthee]

{'furniture': 0.5352066861088035, 'kitchen': 0.4647933138911965}

[benhealthee]

Here is the code:
import spacy
import classy_classification

or import standalon

#from classy_classification import ClassyClassifier
import en_core_web_trf

data = {
"furniture": ["This text is about chairs.",
"Couches, benches and televisions.",
"I really need to get a new sofa."],
"kitchen": ["There also exist things like fridges.",
"I hope to be getting a new stove today.",
"Do you also have some ovens."]
}
nlp = en_core_web_trf.load()

nlp.add_pipe(
"text_categorizer",
config={
"data": data,
"model": "spacy"
}
)

print(nlp("I am looking for kitchen appliances.")._.cats)

[davidberenstein1957]

This was fixed in release 0.6.3 @benhealthee . Thanks for bringing the issue up.