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

# open-hdscan-april3

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/open-hdscan-april3")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 11
* Number of training documents: 2779

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| -1 | models - language - model - llms - language models | 11 | -1_models_language_model_llms | 
| 0 | models - language - model - language models - llms | 792 | 0_models_language_model_language models | 
| 1 | code - models - llms - language - language models | 1082 | 1_code_models_llms_language | 
| 2 | models - quantization - model - training - language | 311 | 2_models_quantization_model_training | 
| 3 | models - bias - text - language - biases | 297 | 3_models_bias_text_language | 
| 4 | brain - models - language - heads - attention | 152 | 4_brain_models_language_heads | 
| 5 | hallucinations - hallucination - models - visual - large | 34 | 5_hallucinations_hallucination_models_visual | 
| 6 | music - audio - poetry - generation - model | 31 | 6_music_audio_poetry_generation | 
| 7 | financial - analysis - sentiment - investment - large | 30 | 7_financial_analysis_sentiment_investment | 
| 8 | editing - knowledge - model editing - editing methods - edit | 25 | 8_editing_knowledge_model editing_editing methods | 
| 9 | materials - molecular - chemical - chemistry - materials science | 14 | 9_materials_molecular_chemical_chemistry |
  
</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