Downloads · 30 days
3
0% of all-time downloads
bertopic-admissions-mmr-keybert
Jsevere/bertopic-admissions-mmr-keybert
bertopic-admissions-mmr-keybert is a machine learning model from Jsevere. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for bertopic.
This model is a fine-tuned BERTopic model for clustering university admissions-related questions and documents using Maximal Marginal Relevance (MMR) and KeyBERT-based keyword generation.
All-time downloads
1K
Public
Parameters
22.7M
237 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors90.9 MB · 99%
At a glance
- Library
- bertopic
- Access
- Public
- Created
- Apr 16, 2025
- Updated
- Apr 18, 2025
- SHA
- f5c7efe6
Model card
From the Hugging Face model README
🧠 bertopic-admissions-mmr-keybert
This model is a fine-tuned BERTopic model for clustering university admissions-related questions and documents using Maximal Marginal Relevance (MMR) and KeyBERT-based keyword generation.
🏗️ Model Details
Base Model: BERTopic (HuggingFace Transformers + UMAP + HDBSCAN)
Embedding Model: all-MiniLM-L6-v2
Keyword Method: MMR + KeyBERT
Training Data: 50-question CSV dataset on university admissions topics
Date Trained: April 2025
📊 Intended Use
- Question clustering for FAQ and chatbot systems
- Identifying user intent for university-related inquiries
🧯 Limitations
- Small training dataset (50 rows)
- English-only
- May group distinct topics if vocabulary overlaps
📁 How to Use
from bertopic import BERTopic
# Load model
topic_model = BERTopic.load("your-local-folder-or-hf-repo-name")
# Transform new docs
topics, probs = topic_model.transform(docs)
- Library
- bertopic
- Created
- Apr 16, 2025
- Updated
- Apr 18, 2025