Add BERTopic model

README.md

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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("davanstrien/transformers_issues_topics")
+
+topic_model.get_topic_info()
+```
+
+## Topic overview
+
+* Number of topics: 30
+* Number of training documents: 7235
+
+<details>
+  <summary>Click here for an overview of all topics.</summary>
+  
+  | 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 |
+  
+</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
+
+## 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

config.json

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+{
+  "calculate_probabilities": false,
+  "language": "english",
+  "low_memory": false,
+  "min_topic_size": 10,
+  "n_gram_range": [
+    1,
+    1
+  ],
+  "nr_topics": 30,
+  "seed_topic_list": null,
+  "top_n_words": 10,
+  "verbose": true,
+  "embedding_model": "sentence-transformers/all-MiniLM-L6-v2"
+}

topic_embeddings.safetensors

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+size 46168