你好！

我正在尝试使用您的库对Yahoo answers主题数据集进行简单的主题建模。目前，我正在尝试使用无监督的方法。在可视化最终的主题时，n_words 参数似乎只更新了绘图内的条形图，而没有更新y轴标签值。以下是代码和最终图像：

from umap import UMAP
from hdbscan import HDBSCAN
from sentence_transformers import SentenceTransformer
from sklearn.cluster import KMeans
from bertopic.representation import MaximalMarginalRelevance
from bertopic import BERTopic
from bertopic.representation import KeyBERTInspired
from datasets import load_dataset
import matplotlib.pyplot as plt

print("Downloading dataset . . .")
data = load_dataset("yahoo_answers_topics", split="test")
text = data.to_pandas()[["best_answer", "topic"]]
num_classes = len(set(text.topic.values))

print("Downloading model . . .")
embedding_model = SentenceTransformer("sentence-transformers/all-mpnet-base-v2")

umap_model = UMAP(
    n_neighbors=15, n_components=5, min_dist=0.0, metric="cosine"
)
kmeans_model = KMeans(n_clusters=num_classes)

representation_model = [
    KeyBERTInspired(), 
    MaximalMarginalRelevance(diversity=0.5)
]

topic_model = BERTopic(
    embedding_model=embedding_model,
    umap_model=umap_model,
    hdbscan_model=kmeans_model,
    representation_model=representation_model,
    verbose=True,
)

print("Finding topics . . .")
topics, probs = topic_model.fit_transform(text.best_answer.values)

fig = topic_model.visualize_barchart(
    top_n_topics=num_classes,
    n_words=10,
)
fig.write_image("topics_barchart.jpg")