I really don't know what you mean by an example. It is a typical huggingface model and can be used as such. More specifically, it is an xtremedistil-l6-h256-uncased trained on the yahoo question answer dataset. If you want to use the model, you could use it with a huggingface pipeline.
from transformers import pipeline import tensorflow as tf max_label_count = 7 sentence = "I need advice for this huggingface model " topicbert = pipeline("text-classification", model="jonaskoenig/topic_classification_04", tokenizer="jonaskoenig/topic_classification_04") top = topicbert(sentence, top_k=max_label_count)
This would give you the top 7 results of the topic classification with their probability.
If you don't know how to use huggingface and models from it, consider reading the documentation, it is really good. If you want to train your models, consider watching this video and try to understand the code.