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transformers_issues_topics

Text Classification
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transformers_issues_topics
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---
tags:
- bertopic
library_name: bertopic
pipeline_tag: text-classification
---

# transformers_issues_topics

This is a [BERTopic](https://github.com/MaartenGr/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("asoria/transformers_issues_topics")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 30
* Number of training documents: 9000

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| -1 | pytorch - tensorflow - bert - tf - pretrained | 15 | -1_pytorch_tensorflow_bert_tf | 
| 0 | bert - bertforsequenceclassification - berttokenizer - bart - batchencodeplus | 2321 | 0_bert_bertforsequenceclassification_berttokenizer_bart | 
| 1 | cuda - memory - trainertrain - tensorflow - trainer | 1554 | 1_cuda_memory_trainertrain_tensorflow | 
| 2 | transformerscli - transformers - transformer - importerror - transformerxl | 882 | 2_transformerscli_transformers_transformer_importerror | 
| 3 | modelcard - modelcards - card - model - models | 490 | 3_modelcard_modelcards_card_model | 
| 4 | gpt2 - gpt2tokenizer - gpt2xl - gpt2tokenizerfast - gpt2model | 462 | 4_gpt2_gpt2tokenizer_gpt2xl_gpt2tokenizerfast | 
| 5 | attributeerror - typeerror - valueerror - runtimeerror - indexerror | 437 | 5_attributeerror_typeerror_valueerror_runtimeerror | 
| 6 | typos - typo - doc - docstring - fix | 336 | 6_typos_typo_doc_docstring | 
| 7 | t5 - t5model - t5base - tf - t5large | 298 | 7_t5_t5model_t5base_tf | 
| 8 | readmemd - readmetxt - readme - modelcard - file | 270 | 8_readmemd_readmetxt_readme_modelcard | 
| 9 | ci - testing - tests - test - speedup | 254 | 9_ci_testing_tests_test | 
| 10 | s2s - s2sdistill - s2t - s2strainer - exampless2s | 245 | 10_s2s_s2sdistill_s2t_s2strainer | 
| 11 | glue - gluepy - glueconvertexamplestofeatures - roberta - huggingfacetransformers | 214 | 11_glue_gluepy_glueconvertexamplestofeatures_roberta | 
| 12 | ner - pipeline - pipelines - nerpipeline - fillmaskpipeline | 158 | 12_ner_pipeline_pipelines_nerpipeline | 
| 13 | rag - ragtokenforgeneration - ragsequenceforgeneration - clean - tests | 153 | 13_rag_ragtokenforgeneration_ragsequenceforgeneration_clean | 
| 14 | questionansweringpipeline - questionanswering - answering - tfalbertforquestionanswering - questionasnwering | 143 | 14_questionansweringpipeline_questionanswering_answering_tfalbertforquestionanswering | 
| 15 | onnx - 04onnxexport - 04onnxexportipynb - aionnx - sphynx | 131 | 15_onnx_04onnxexport_04onnxexportipynb_aionnx | 
| 16 | longformer - longformers - longform - longformerlayer - longformermodel | 104 | 16_longformer_longformers_longform_longformerlayer | 
| 17 | labelsmoothednllloss - label - labelsmoothingfactor - labels - labelsmoothing | 76 | 17_labelsmoothednllloss_label_labelsmoothingfactor_labels | 
| 18 | benchmark - benchmarking - benchmarks - accuracy - evaluation | 73 | 18_benchmark_benchmarking_benchmarks_accuracy | 
| 19 | wav2vec2 - wav2vec - wav2vec20 - wav2vec2forctc - wav2vec2xlrswav2vec2 | 67 | 19_wav2vec2_wav2vec_wav2vec20_wav2vec2forctc | 
| 20 | flax - flaxelectraformaskedlm - flaxelectraforpretraining - flaxjax - flaxelectramodel | 51 | 20_flax_flaxelectraformaskedlm_flaxelectraforpretraining_flaxjax | 
| 21 | configpath - configs - config - configuration - modelconfigs | 49 | 21_configpath_configs_config_configuration | 
| 22 | logging - logs - log - logger - loghistory | 40 | 22_logging_logs_log_logger | 
| 23 | cachedir - cache - cachedpath - caching - cached | 38 | 23_cachedir_cache_cachedpath_caching | 
| 24 | wandbproject - wandb - sagemaker - sagemakertrainer - wandbcallback | 36 | 24_wandbproject_wandb_sagemaker_sagemakertrainer | 
| 25 | notebook - notebooks - community - colab - t5 | 33 | 25_notebook_notebooks_community_colab | 
| 26 | electra - electrapretrainedmodel - electraformaskedlm - electraformultiplechoice - electrafortokenclassification | 30 | 26_electra_electrapretrainedmodel_electraformaskedlm_electraformultiplechoice | 
| 27 | layoutlm - layout - layoutlmtokenizer - layoutlmbaseuncased - tf | 25 | 27_layoutlm_layout_layoutlmtokenizer_layoutlmbaseuncased | 
| 28 | pplm - pr - deprecated - variable - ppl | 15 | 28_pplm_pr_deprecated_variable |
  
</details>

## 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: 1.26.4
* HDBSCAN: 0.8.38.post1
* UMAP: 0.5.6
* Pandas: 2.1.4
* Scikit-Learn: 1.5.2
* Sentence-transformers: 3.1.1
* Transformers: 4.44.2
* Numba: 0.60.0
* Plotly: 5.24.1
* Python: 3.10.12