---
tags:
- bertopic
library_name: bertopic
pipeline_tag: text-classification
---

# general-april-3

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("Thang203/general-april-3")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 11
* Number of training documents: 6795

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| 0 | financial - legal - summarization - models - llms | 251 | 0_financial_legal_summarization_models | 
| 1 | reasoning - models - language - llms - language models | 887 | 1_reasoning_models_language_llms | 
| 2 | models - llms - attacks - attack - language | 467 | 2_models_llms_attacks_attack | 
| 3 | models - model - training - language - inference | 528 | 3_models_model_training_language | 
| 4 | language - models - llms - human - model | 638 | 4_language_models_llms_human | 
| 5 | medical - clinical - models - language - llms | 524 | 5_medical_clinical_models_language | 
| 6 | visual - multimodal - models - image - language | 630 | 6_visual_multimodal_models_image | 
| 7 | code - generation - code generation - llms - models | 417 | 7_code_generation_code generation_llms | 
| 8 | models - language - language models - model - llms | 1232 | 8_models_language_language models_model | 
| 9 | chatgpt - ai - students - education - generative | 542 | 9_chatgpt_ai_students_education | 
| 10 | models - chatgpt - language - ai - llms | 679 | 10_models_chatgpt_language_ai |
  
</details>

## Training hyperparameters

* calculate_probabilities: False
* language: english
* low_memory: False
* min_topic_size: 10
* n_gram_range: (1, 1)
* nr_topics: 11
* seed_topic_list: None
* top_n_words: 10
* verbose: True
* zeroshot_min_similarity: 0.7
* zeroshot_topic_list: None

## Framework versions

* Numpy: 1.25.2
* HDBSCAN: 0.8.33
* UMAP: 0.5.6
* Pandas: 2.0.3
* Scikit-Learn: 1.2.2
* Sentence-transformers: 2.6.1
* Transformers: 4.38.2
* Numba: 0.58.1
* Plotly: 5.15.0
* Python: 3.10.12