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---
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
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