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---
tags:
- bertopic
library_name: bertopic
pipeline_tag: text-classification
---
# recipecomments-bertopic
This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model.
BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets.
## Usage
To use this model, please install BERTopic:
```
pip install -U bertopic
```
You can use the model as follows:
```python
from bertopic import BERTopic
topic_model = BERTopic.load("daveripper0020/recipecomments-bertopic")
topic_model.get_topic_info()
```
## Topic overview
* Number of topics: 6
* Number of training documents: 386
<details>
<summary>Click here for an overview of all topics.</summary>
| Topic ID | Topic Keywords | Topic Frequency | Label |
|----------|----------------|-----------------|-------|
| -1 | ๋ธ๋ก๊ทธ - ์ดํ - ๋ง์ด - ๊น์ง - ํญ์ | 12 | -1_๋ธ๋ก๊ทธ_์ดํ_๋ง์ด_๊น์ง |
| 0 | ์ผ๋ฏผ - ์ถ์ฅ - ์ธ๊ฐ์ - ๋๋ฑ - ๋๋ฌด | 54 | 0_์ผ๋ฏผ_์ถ์ฅ_์ธ๊ฐ์_๋๋ฑ |
| 1 | ๋๋ฑ - ์ผ๋ฏผ - ์ถ์ฅ - ์๋ฆฌ - ์์ต | 151 | 1_๋๋ฑ_์ผ๋ฏผ_์ถ์ฅ_์๋ฆฌ |
| 2 | ์ฐ๋ญ - ๋ง๋ - ๋ ์ํผ - ๋ฃ๊ณ - ๊ฐ์ฅ | 77 | 2_์ฐ๋ญ_๋ง๋_๋ ์ํผ_๋ฃ๊ณ |
| 3 | ๋ง์์ด์ - ์ง์ง - ๋จน์๋๋ฐ - ๊ฐ๋จํ๊ณ - ๋๋ฌด | 76 | 3_๋ง์์ด์_์ง์ง_๋จน์๋๋ฐ_๊ฐ๋จํ๊ณ |
| 4 | ๊ฐ์ฌํฉ๋๋ค - ํฉ๋๋ค - ์๋ - ์ ๋ฆฌ - ๋ฏฟ๋ | 16 | 4_๊ฐ์ฌํฉ๋๋ค_ํฉ๋๋ค_์๋_์ ๋ฆฌ |
</details>
## Training hyperparameters
* calculate_probabilities: True
* language: None
* low_memory: False
* min_topic_size: 10
* n_gram_range: (1, 1)
* nr_topics: None
* seed_topic_list: None
* top_n_words: 10
* verbose: False
## Framework versions
* Numpy: 1.23.5
* HDBSCAN: 0.8.33
* UMAP: 0.5.4
* Pandas: 1.5.3
* Scikit-Learn: 1.2.2
* Sentence-transformers: 2.2.2
* Transformers: 4.35.1
* Numba: 0.58.1
* Plotly: 5.15.0
* Python: 3.10.12
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