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--- |
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tags: |
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- bertopic |
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library_name: bertopic |
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pipeline_tag: text-classification |
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--- |
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# industry-mar11Top10 |
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This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model. |
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BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets. |
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## Usage |
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To use this model, please install BERTopic: |
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``` |
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pip install -U bertopic |
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``` |
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You can use the model as follows: |
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```python |
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from bertopic import BERTopic |
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topic_model = BERTopic.load("Thang203/industry-mar11Top10") |
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topic_model.get_topic_info() |
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``` |
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## Topic overview |
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* Number of topics: 10 |
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* Number of training documents: 516 |
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<details> |
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<summary>Click here for an overview of all topics.</summary> |
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| Topic ID | Topic Keywords | Topic Frequency | Label | |
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|----------|----------------|-----------------|-------| |
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| -1 | models - language - data - large - language models | 15 | -1_models_language_data_large | |
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| 0 | models - model - language - training - language models | 169 | 0_models_model_language_training | |
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| 1 | code - language - models - llms - programming | 118 | 1_code_language_models_llms | |
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| 2 | ai - models - language - dialogue - human | 49 | 2_ai_models_language_dialogue | |
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| 3 | detection - models - text - language - model | 47 | 3_detection_models_text_language | |
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| 4 | multimodal - visual - image - models - generation | 32 | 4_multimodal_visual_image_models | |
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| 5 | agents - language - policy - learning - tasks | 24 | 5_agents_language_policy_learning | |
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| 6 | speech - asr - text - speaker - recognition | 22 | 6_speech_asr_text_speaker | |
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| 7 | reasoning - cot - models - problems - commonsense | 21 | 7_reasoning_cot_models_problems | |
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| 8 | retrieval - information - query - llms - models | 19 | 8_retrieval_information_query_llms | |
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</details> |
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## Training hyperparameters |
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* calculate_probabilities: False |
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* language: english |
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* low_memory: False |
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* min_topic_size: 10 |
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* n_gram_range: (1, 1) |
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* nr_topics: 10 |
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* seed_topic_list: None |
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* top_n_words: 10 |
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* verbose: True |
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* zeroshot_min_similarity: 0.7 |
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* zeroshot_topic_list: None |
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## Framework versions |
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* Numpy: 1.25.2 |
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* HDBSCAN: 0.8.33 |
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* UMAP: 0.5.5 |
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* Pandas: 1.5.3 |
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* Scikit-Learn: 1.2.2 |
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* Sentence-transformers: 2.6.1 |
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* Transformers: 4.38.2 |
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* Numba: 0.58.1 |
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* Plotly: 5.15.0 |
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* Python: 3.10.12 |
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