janko/s3_scriptum
0
pipelinetag: text-classification libraryname: turftopic tags:
- turftopic
- topic-modelling ---
janko/s3_scriptum
This repository contains a topic model trained with the Turftopic Python library.
To load and use the model run the following piece of code:
from turftopic import load_model
model = load_model(janko/s3_scriptum)
model.print_topics()Model Structure
The model is structured as follows:
SemanticSignalSeparation(decomposition=FastICA(n_components=10),
encoder=SentenceTransformer(
(0): Transformer({'max_seq_length': 8192, 'do_lower_case': False}) with Transformer model: XLMRobertaModel
(1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_s...
'about': 4,
'abraham': 5,
'abrahama': 6,
'abroad': 7,
'absence': 8,
'abso': 9,
'absolutismus': 10,
'absolutna': 11,
'absolutno': 12,
'absolutní': 13,
'absolutorium': 14,
'absolvent': 15,
'absolvovat': 16,
'absolvování': 17,
'abstinent': 18,
'abstrakce': 19,
'abstraktní': 20,
'absurdita': 21,
'absurdnost': 22,
'absurdní': 23,
'absurdum': 24,
'abv': 25,
'abych': 26,
'abys': 27,
'abyst': 28,
'ac': 29, ...}))Topics
The topics discovered by the model are the following:
Package versions
The model in this repo was trained using the following package versions:
We recommend that you install the same, or compatible versions of these packages locally, before trying to load a model.
