--- tags: - bertopic library_name: bertopic pipeline_tag: text-classification --- # industry-mar11Top10 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-mar11Top10") topic_model.get_topic_info() ``` ## Topic overview * Number of topics: 10 * Number of training documents: 516
Click here for an overview of all topics. | Topic ID | Topic Keywords | Topic Frequency | Label | |----------|----------------|-----------------|-------| | -1 | models - language - data - large - language models | 15 | -1_models_language_data_large | | 0 | models - model - language - training - language models | 169 | 0_models_model_language_training | | 1 | code - language - models - llms - programming | 118 | 1_code_language_models_llms | | 2 | ai - models - language - dialogue - human | 49 | 2_ai_models_language_dialogue | | 3 | detection - models - text - language - model | 47 | 3_detection_models_text_language | | 4 | multimodal - visual - image - models - generation | 32 | 4_multimodal_visual_image_models | | 5 | agents - language - policy - learning - tasks | 24 | 5_agents_language_policy_learning | | 6 | speech - asr - text - speaker - recognition | 22 | 6_speech_asr_text_speaker | | 7 | reasoning - cot - models - problems - commonsense | 21 | 7_reasoning_cot_models_problems | | 8 | retrieval - information - query - llms - models | 19 | 8_retrieval_information_query_llms |
## Training hyperparameters * calculate_probabilities: False * language: english * low_memory: False * min_topic_size: 10 * n_gram_range: (1, 1) * nr_topics: 10 * 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