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

# industry-mar11

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/industry-mar11")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 12
* Number of training documents: 516

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| -1 | models - language - data - large - language models | 51 | -1_models_language_data_large | 
| 0 | multimodal - visual - image - models - generation | 169 | 0_multimodal_visual_image_models | 
| 1 | speech - asr - text - speaker - recognition | 24 | 1_speech_asr_text_speaker | 
| 2 | detection - models - text - language - model | 21 | 2_detection_models_text_language | 
| 3 | code - language - llms - models - programming | 32 | 3_code_language_llms_models | 
| 4 | agents - policy - language - learning - tasks | 49 | 4_agents_policy_language_learning | 
| 5 | reasoning - cot - problems - models - commonsense | 22 | 5_reasoning_cot_problems_models | 
| 6 | retrieval - information - query - llms - queries | 19 | 6_retrieval_information_query_llms | 
| 7 | ai - models - language - dialogue - human | 15 | 7_ai_models_language_dialogue | 
| 8 | language - models - translation - model - language models | 47 | 8_language_models_translation_model | 
| 9 | distillation - model - knowledge - pretrained - student | 51 | 9_distillation_model_knowledge_pretrained | 
| 10 | training - model - models - transformer - language | 16 | 10_training_model_models_transformer |
  
</details>

## Training hyperparameters

* calculate_probabilities: False
* language: english
* low_memory: False
* min_topic_size: 10
* n_gram_range: (1, 1)
* nr_topics: 20
* 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: 0.5.5
* Pandas: 1.5.3
* 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
