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("davanstrien/transformers_issues_topics")
topic_model.get_topic_info()
Topic overview
- Number of topics: 30
- Number of training documents: 7235
Click here for an overview of all topics.
Topic ID | Topic Keywords | Topic Frequency | Label |
---|---|---|---|
-1 | encoder - bert - tensorflow - decoder - output | 11 | -1_encoder_bert_tensorflow_decoder |
0 | tokenizer - tokenizers - tokenization - tokenize - berttokenizer | 2265 | 0_tokenizer_tokenizers_tokenization_tokenize |
1 | cuda - runtimeerror - conda - pytorch - tensorflow | 1513 | 1_cuda_runtimeerror_conda_pytorch |
2 | readmemd - readmetxt - readme - docstring - docstrings | 763 | 2_readmemd_readmetxt_readme_docstring |
3 | trainertrain - trainer - trainertfpy - trainers - training | 550 | 3_trainertrain_trainer_trainertfpy_trainers |
4 | rag - roberta - robertatokenizer - robertatokenizerfast - robertabase | 546 | 4_rag_roberta_robertatokenizer_robertatokenizerfast |
5 | modelcard - modelcards - card - model - cards | 473 | 5_modelcard_modelcards_card_model |
6 | importerror - transformerscli - transformers - transformerxl - transformer | 432 | 6_importerror_transformerscli_transformers_transformerxl |
7 | seq2seq - seq2seqtrainer - seq2seqdataset - runseq2seq - examplesseq2seq | 405 | 7_seq2seq_seq2seqtrainer_seq2seqdataset_runseq2seq |
8 | gpt2 - gpt2tokenizer - gpt2xl - gpt2tokenizerfast - gpt | 365 | 8_gpt2_gpt2tokenizer_gpt2xl_gpt2tokenizerfast |
9 | t5 - t5model - t5base - t5large - tf | 289 | 9_t5_t5model_t5base_t5large |
10 | tests - testing - speedup - test - testgeneratefp16 | 230 | 10_tests_testing_speedup_test |
11 | questionansweringpipeline - questionanswering - answering - questionasnwering - distilbertforquestionanswering | 138 | 11_questionansweringpipeline_questionanswering_answering_questionasnwering |
12 | ner - pipeline - pipelinener - pipelines - pipelineframework | 138 | 12_ner_pipeline_pipelinener_pipelines |
13 | deberta - debertav2 - debertav2initpy - debertatokenizer - distilbertmodel | 132 | 13_deberta_debertav2_debertav2initpy_debertatokenizer |
14 | onnxonnxruntime - onnx - onnxexport - 04onnxexport - 04onnxexportipynb | 110 | 14_onnxonnxruntime_onnx_onnxexport_04onnxexport |
15 | benchmark - benchmarks - accuracy - precision - comparison | 85 | 15_benchmark_benchmarks_accuracy_precision |
16 | labelsmoothingfactor - labelsmoothednllloss - labelsmoothing - labels - label | 79 | 16_labelsmoothingfactor_labelsmoothednllloss_labelsmoothing_labels |
17 | longformer - longformers - longform - longformerforqa - longformerlayer | 71 | 17_longformer_longformers_longform_longformerforqa |
18 | generationbeamsearchpy - generatebeamsearch - beamsearch - nonbeamsearch - beam | 60 | 18_generationbeamsearchpy_generatebeamsearch_beamsearch_nonbeamsearch |
19 | cachedir - cache - cachedpath - caching - cached | 58 | 19_cachedir_cache_cachedpath_caching |
20 | wav2vec2 - wav2vec - wav2vec20 - wav2vec2forctc - wav2vec2xlrswav2vec2 | 56 | 20_wav2vec2_wav2vec_wav2vec20_wav2vec2forctc |
21 | flax - flaxelectraformaskedlm - flaxelectraforpretraining - flaxjax - flaxelectramodel | 52 | 21_flax_flaxelectraformaskedlm_flaxelectraforpretraining_flaxjax |
22 | wandbproject - wandb - wandbcallback - wandbdisabled - wandbdisabledtrue | 49 | 22_wandbproject_wandb_wandbcallback_wandbdisabled |
23 | electra - electrapretrainedmodel - electraformaskedlm - electraformultiplechoice - electrafortokenclassification | 38 | 23_electra_electrapretrainedmodel_electraformaskedlm_electraformultiplechoice |
24 | layoutlm - layout - layoutlmtokenizer - layoutlmbaseuncased - tf | 24 | 24_layoutlm_layout_layoutlmtokenizer_layoutlmbaseuncased |
25 | notebook - notebooks - community - text - multilabel | 18 | 25_notebook_notebooks_community_text |
26 | dict - dictstr - returndict - parse - arguments | 18 | 26_dict_dictstr_returndict_parse |
27 | pplm - pr - deprecated - variable - ppl | 17 | 27_pplm_pr_deprecated_variable |
28 | isort - github - repo - version - setupcfg | 15 | 28_isort_github_repo_version |
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
Framework versions
- Numpy: 1.22.4
- HDBSCAN: 0.8.29
- UMAP: 0.5.3
- Pandas: 1.5.3
- Scikit-Learn: 1.2.2
- Sentence-transformers: 2.2.2
- Transformers: 4.29.2
- Numba: 0.56.4
- Plotly: 5.13.1
- Python: 3.10.11
- Downloads last month
- 46
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.