You can deploy this model and start earning money today!

Thang203/
industry-mar11

Name: industry-mar11
Availability: InStock

bertopic

text-classification

Views

No views yet

industry-mar11

This is a 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

Click here for an overview of all topics.

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

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