arxiv_scientific_abstract_berttopic_model
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:
from bertopic import BERTopic
topic_model = BERTopic.load("Rchamba/arxiv_scientific_abstract_berttopic_model")
topic_model.get_topic_info()
Topic overview
- Number of topics: 46
- Number of training documents: 1463
Click here for an overview of all topics.
Topic ID | Topic Keywords | Topic Frequency | Label |
---|---|---|---|
-1 | data - probability - learning - paper - theory | 10 | -1_data_probability_learning_paper |
0 | quantum - classical - computing - computation - measurement | 233 | 0_quantum_classical_computing_computation |
1 | logic - computability - cl - computational - problems | 170 | 1_logic_computability_cl_computational |
2 | web - semantic - concept - ontology - flow | 130 | 2_web_semantic_concept_ontology |
3 | belief - probability - causal - chain - graphs | 51 | 3_belief_probability_causal_chain |
4 | spaces - informal - notes - lie - topological | 51 | 4_spaces_informal_notes_lie |
5 | evolutionary - selection - evolution - cultural - fitness | 44 | 5_evolutionary_selection_evolution_cultural |
6 | secret - steganography - data - random - rate | 42 | 6_secret_steganography_data_random |
7 | learning - prediction - universal - sequence - reinforcement | 37 | 7_learning_prediction_universal_sequence |
8 | rationality - intelligence - ai - rational - human | 36 | 8_rationality_intelligence_ai_rational |
9 | obstacle - wave - inverse - scattering - data | 34 | 9_obstacle_wave_inverse_scattering |
10 | deep - neural - learning - dnn - speech | 32 | 10_deep_neural_learning_dnn |
11 | regression - lasso - functional - estimator - changepoints | 32 | 11_regression_lasso_functional_estimator |
12 | brain - mental - human - psychological - neural | 26 | 12_brain_mental_human_psychological |
13 | sp - compression - icmaus - intelligence - reasoning | 25 | 13_sp_compression_icmaus_intelligence |
14 | bg - systems - sq - statistical - mechanics | 24 | 14_bg_systems_sq_statistical |
15 | tetraquark - rm - gamma - type - qcd | 23 | 15_tetraquark_rm_gamma_type |
16 | combinatorial - design - problems - clustering - modular | 23 | 16_combinatorial_design_problems_clustering |
17 | meson - spin - parton - polarized - asymmetry | 21 | 17_meson_spin_parton_polarized |
18 | keyphrases - word - similarity - semantic - algorithm | 21 | 18_keyphrases_word_similarity_semantic |
19 | communication - complexity - consciousness - systems - meaning | 21 | 19_communication_complexity_consciousness_systems |
20 | scalar - initial - compact - angular - stationary | 21 | 20_scalar_initial_compact_angular |
21 | orbital - earth - satellites - postnewtonian - lageos | 21 | 21_orbital_earth_satellites_postnewtonian |
22 | gate - phi - ring - flux - magnetic | 21 | 22_gate_phi_ring_flux |
23 | hole - black - horizon - radiation - hawking | 19 | 23_hole_black_horizon_radiation |
24 | citation - journals - journal - science - indicators | 19 | 24_citation_journals_journal_science |
25 | randomness - algorithmic - turings - science - complexity | 18 | 25_randomness_algorithmic_turings_science |
26 | ultrametric - data - ultrametricity - hierarchical - padic | 18 | 26_ultrametric_data_ultrametricity_hierarchical |
27 | kernel - kernels - gmm - datasets - submodular | 17 | 27_kernel_kernels_gmm_datasets |
28 | neutrosophic - fuzzy - valued - intuitionistic - logic | 17 | 28_neutrosophic_fuzzy_valued_intuitionistic |
29 | impulse - process - entropy - observer - functional | 16 | 29_impulse_process_entropy_observer |
30 | users - recommender - situation - user - access | 16 | 30_users_recommender_situation_user |
31 | physical - universe - physics - laws - computation | 14 | 31_physical_universe_physics_laws |
32 | engines - search - queries - google - ranking | 14 | 32_engines_search_queries_google |
33 | chiral - pi - rightarrow - axialvector - mesons | 13 | 33_chiral_pi_rightarrow_axialvector |
34 | nf - anomalous - operators - msbar - point | 13 | 34_nf_anomalous_operators_msbar |
35 | hypersurfaces - curvature - manifolds - manifold - chern | 13 | 35_hypersurfaces_curvature_manifolds_manifold |
36 | seti - future - paradox - extraterrestrial - anthropic | 13 | 36_seti_future_paradox_extraterrestrial |
37 | torsion - density - spintorsion - cobe - sitter | 13 | 37_torsion_density_spintorsion_cobe |
38 | sigma - pipi - kk - elastic - data | 13 | 38_sigma_pipi_kk_elastic |
39 | idempotent - solution - tropical - linear - problems | 12 | 39_idempotent_solution_tropical_linear |
40 | clustering - reports - clusters - dempstershafer - cluster | 12 | 40_clustering_reports_clusters_dempstershafer |
41 | wormhole - wormholes - traversable - solutions - exact | 11 | 41_wormhole_wormholes_traversable_solutions |
42 | turbulence - temperature - years - fluctuations - detrended | 11 | 42_turbulence_temperature_years_fluctuations |
43 | scheduling - search - local - multiobjective - maker | 11 | 43_scheduling_search_local_multiobjective |
44 | chemical - thermodynamic - equilibrium - laser - thermodynamics | 11 | 44_chemical_thermodynamic_equilibrium_laser |
Training hyperparameters
- calculate_probabilities: True
- language: english
- low_memory: False
- min_topic_size: 10
- n_gram_range: (1, 1)
- nr_topics: None
- seed_topic_list: None
- top_n_words: 10
- verbose: False
- zeroshot_min_similarity: 0.7
- zeroshot_topic_list: None
Framework versions
- Numpy: 2.0.2
- HDBSCAN: 0.8.40
- UMAP: 0.5.7
- Pandas: 2.2.2
- Scikit-Learn: 1.6.1
- Sentence-transformers: 4.1.0
- Transformers: 4.52.4
- Numba: 0.60.0
- Plotly: 5.24.1
- Python: 3.11.13
- Downloads last month
- 2
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
๐
Ask for provider support