Spaces:
Runtime error
Runtime error
Update app.py
Browse files
app.py
CHANGED
|
@@ -53,21 +53,27 @@ top_n = form.number_input("What's the max length of the text?", value = 10)
|
|
| 53 |
form.form_submit_button("Run")
|
| 54 |
|
| 55 |
if ebay_topic == "Motor":
|
|
|
|
| 56 |
topics, probs = fit_transform(topic_model, tiktok)
|
| 57 |
similar_topics, similarity = topic_model.find_topics("Motor", top_n=top_n)
|
| 58 |
elif ebay_topic == "Bicycle":
|
|
|
|
| 59 |
topics, probs = fit_transform(topic_model, tiktok)
|
| 60 |
similar_topics, similarity = topic_model.find_topics("Bicycle", top_n=top_n)
|
| 61 |
elif ebay_topic == "Beauty":
|
|
|
|
| 62 |
topics, probs = fit_transform(topic_model, tiktok)
|
| 63 |
similar_topics, similarity = topic_model.find_topics("Beauty", top_n=top_n)
|
| 64 |
elif ebay_topic == "Basketball":
|
|
|
|
| 65 |
topics, probs = fit_transform(topic_model, tiktok)
|
| 66 |
similar_topics, similarity = topic_model.find_topics("Basketball", top_n=top_n)
|
| 67 |
elif ebay_topic == "Fitness":
|
|
|
|
| 68 |
topics, probs = fit_transform(topic_model, tiktok)
|
| 69 |
similar_topics, similarity = topic_model.find_topics("Fitness", top_n=top_n)
|
| 70 |
else:
|
|
|
|
| 71 |
topics, probs = fit_transform(topic_model, tiktok)
|
| 72 |
similar_topics, similarity = topic_model.find_topics("Motor", top_n=top_n)
|
| 73 |
|
|
|
|
| 53 |
form.form_submit_button("Run")
|
| 54 |
|
| 55 |
if ebay_topic == "Motor":
|
| 56 |
+
topic_model = BERTopic(verbose=True,vectorizer_model=vectorizer_model)
|
| 57 |
topics, probs = fit_transform(topic_model, tiktok)
|
| 58 |
similar_topics, similarity = topic_model.find_topics("Motor", top_n=top_n)
|
| 59 |
elif ebay_topic == "Bicycle":
|
| 60 |
+
topic_model = BERTopic(verbose=True,vectorizer_model=vectorizer_model)
|
| 61 |
topics, probs = fit_transform(topic_model, tiktok)
|
| 62 |
similar_topics, similarity = topic_model.find_topics("Bicycle", top_n=top_n)
|
| 63 |
elif ebay_topic == "Beauty":
|
| 64 |
+
topic_model = BERTopic(verbose=True,vectorizer_model=vectorizer_model)
|
| 65 |
topics, probs = fit_transform(topic_model, tiktok)
|
| 66 |
similar_topics, similarity = topic_model.find_topics("Beauty", top_n=top_n)
|
| 67 |
elif ebay_topic == "Basketball":
|
| 68 |
+
topic_model = BERTopic(verbose=True,vectorizer_model=vectorizer_model)
|
| 69 |
topics, probs = fit_transform(topic_model, tiktok)
|
| 70 |
similar_topics, similarity = topic_model.find_topics("Basketball", top_n=top_n)
|
| 71 |
elif ebay_topic == "Fitness":
|
| 72 |
+
topic_model = BERTopic(verbose=True,vectorizer_model=vectorizer_model)
|
| 73 |
topics, probs = fit_transform(topic_model, tiktok)
|
| 74 |
similar_topics, similarity = topic_model.find_topics("Fitness", top_n=top_n)
|
| 75 |
else:
|
| 76 |
+
topic_model = BERTopic(verbose=True,vectorizer_model=vectorizer_model)
|
| 77 |
topics, probs = fit_transform(topic_model, tiktok)
|
| 78 |
similar_topics, similarity = topic_model.find_topics("Motor", top_n=top_n)
|
| 79 |
|