transformers_issues_topics
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("noumanjavaid/transformers_issues_topics")
topic_model.get_topic_info()
Topic overview
- Number of topics: 30
- Number of training documents: 9000
Click here for an overview of all topics.
Topic ID | Topic Keywords | Topic Frequency | Label |
---|---|---|---|
-1 | models - bert - model - tensorflow - tokenizers | 14 | -1_models_bert_model_tensorflow |
0 | tokenizer - tokenizers - tokenization - token - tokens | 2078 | 0_tokenizer_tokenizers_tokenization_token |
1 | pytorch - tensorflow - modelingutilspy - attributeerror - runtimeerror | 1886 | 1_pytorch_tensorflow_modelingutilspy_attributeerror |
2 | trainertrain - trainer - trainers - training - evaluateduringtraining | 696 | 2_trainertrain_trainer_trainers_training |
3 | summarization - summaries - summary - examples - sentencepiece | 636 | 3_summarization_summaries_summary_examples |
4 | gpt2tokenizer - gpt2 - gpt2tokenizerfast - gpt2model - gpt | 452 | 4_gpt2tokenizer_gpt2_gpt2tokenizerfast_gpt2model |
5 | modelcard - modelcards - card - model - models | 451 | 5_modelcard_modelcards_card_model |
6 | typos - typo - fix - correction - fixed | 446 | 6_typos_typo_fix_correction |
7 | readmemd - readmetxt - readme - modelcard - file | 284 | 7_readmemd_readmetxt_readme_modelcard |
8 | t5 - t5model - t5base - tf - t5large | 256 | 8_t5_t5model_t5base_tf |
9 | longformer - longformers - longformerformultiplechoice - longformertokenizerfast - attentions | 254 | 9_longformer_longformers_longformerformultiplechoice_longformertokenizerfast |
10 | seq2seq - seq2seqtrainer - seq2seqdataset - seq2seqfinetunepy - runseq2seq | 223 | 10_seq2seq_seq2seqtrainer_seq2seqdataset_seq2seqfinetunepy |
11 | pipeline - pipelines - ner - pipelinesentimentanalysis - nerpipeline | 209 | 11_pipeline_pipelines_ner_pipelinesentimentanalysis |
12 | ci - testing - tests - test - testgeneratefp16 | 175 | 12_ci_testing_tests_test |
13 | deprecate - deprecation - deprecated - warnings - warning | 136 | 13_deprecate_deprecation_deprecated_warnings |
14 | onnxonnxruntime - onnx - 04onnxexport - 04onnxexportipynb - benchmarkonnxexport | 129 | 14_onnxonnxruntime_onnx_04onnxexport_04onnxexportipynb |
15 | datacollatorforlanguagemodelingfile - datacollatorforlanguagemodeling - datacollatorforlanguagemodelling - datacollatorforpermutationlanguagemodeling - labelsmoothingfactor | 100 | 15_datacollatorforlanguagemodelingfile_datacollatorforlanguagemodeling_datacollatorforlanguagemodelling_datacollatorforpermutationlanguagemodeling |
16 | deberta - debertav2 - debertav2initpy - debertatokenizer - debertav2xxlargemnli | 73 | 16_deberta_debertav2_debertav2initpy_debertatokenizer |
17 | benchmark - benchmarking - benchmarks - comparison - results | 63 | 17_benchmark_benchmarking_benchmarks_comparison |
18 | generationbeamsearchpy - generatebeamsearch - generatebeamsearchoutputs - beamsearch - nonbeamsearch | 61 | 18_generationbeamsearchpy_generatebeamsearch_generatebeamsearchoutputs_beamsearch |
19 | wandbproject - wandb - wandbcallback - wandbdisabled - wandbdisabledtrue | 56 | 19_wandbproject_wandb_wandbcallback_wandbdisabled |
20 | wav2vec2 - wav2vec - wav2vec20 - wav2vec2forctc - wav2vec2xlrswav2vec2 | 54 | 20_wav2vec2_wav2vec_wav2vec20_wav2vec2forctc |
21 | flax - flaxelectraformaskedlm - flaxelectraforpretraining - flaxjax - flaxelectramodel | 49 | 21_flax_flaxelectraformaskedlm_flaxelectraforpretraining_flaxjax |
22 | configpath - configs - config - configuration - modelconfigs | 49 | 22_configpath_configs_config_configuration |
23 | logging - logs - log - logger - loggingfirststep | 45 | 23_logging_logs_log_logger |
24 | cachedir - cache - cachedpath - caching - cached | 34 | 24_cachedir_cache_cachedpath_caching |
25 | electra - electrapretrainedmodel - electraformaskedlm - electraformultiplechoice - electrafortokenclassification | 34 | 25_electra_electrapretrainedmodel_electraformaskedlm_electraformultiplechoice |
26 | layoutlm - layoutlmtokenizer - layout - layoutlmbaseuncased - tf | 23 | 26_layoutlm_layoutlmtokenizer_layout_layoutlmbaseuncased |
27 | dict - dictstr - returndict - parse - arguments | 17 | 27_dict_dictstr_returndict_parse |
28 | pplm - pr - deprecated - variable - ppl | 17 | 28_pplm_pr_deprecated_variable |
Training hyperparameters
- calculate_probabilities: False
- language: english
- low_memory: False
- min_topic_size: 10
- n_gram_range: (1, 1)
- nr_topics: 30
- 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: 0.8.37
- UMAP: 0.5.6
- Pandas: 2.0.3
- Scikit-Learn: 1.2.2
- Sentence-transformers: 3.0.1
- Transformers: 4.41.2
- Numba: 0.58.1
- Plotly: 5.15.0
- Python: 3.10.12
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