|
|
|
|
|
--- |
|
|
tags: |
|
|
- bertopic |
|
|
library_name: bertopic |
|
|
pipeline_tag: text-classification |
|
|
--- |
|
|
|
|
|
# close-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/close-hdscan-april3") |
|
|
|
|
|
topic_model.get_topic_info() |
|
|
``` |
|
|
|
|
|
## Topic overview |
|
|
|
|
|
* Number of topics: 11 |
|
|
* Number of training documents: 5027 |
|
|
|
|
|
<details> |
|
|
<summary>Click here for an overview of all topics.</summary> |
|
|
|
|
|
| Topic ID | Topic Keywords | Topic Frequency | Label | |
|
|
|----------|----------------|-----------------|-------| |
|
|
| -1 | models - language - llms - language models - large | 11 | -1_models_language_llms_language models | |
|
|
| 0 | models - language - llms - language models - large | 1484 | 0_models_language_llms_language models | |
|
|
| 1 | chatgpt - models - ai - language - llms | 2023 | 1_chatgpt_models_ai_language | |
|
|
| 2 | visual - models - multimodal - image - graph | 589 | 2_visual_models_multimodal_image | |
|
|
| 3 | llms - attacks - attack - models - adversarial | 317 | 3_llms_attacks_attack_models | |
|
|
| 4 | code - generation - code generation - software - models | 273 | 4_code_generation_code generation_software | |
|
|
| 5 | design - creative - ai - ideas - music | 229 | 5_design_creative_ai_ideas | |
|
|
| 6 | robot - dialogue - round - robots - preliminary | 60 | 6_robot_dialogue_round_robots | |
|
|
| 7 | causal - causality - causal reasoning - llms - causal inference | 15 | 7_causal_causality_causal reasoning_llms | |
|
|
| 8 | astronomy - scientific - data - knowledge - generative | 14 | 8_astronomy_scientific_data_knowledge | |
|
|
| 9 | urban - traffic - foundation models - foundation - transportation | 12 | 9_urban_traffic_foundation models_foundation | |
|
|
|
|
|
</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 |
|
|
|
