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("lbhjvh14/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 | pretrained - tokenizer - tensorflow - tokenizers - tf | 11 | -1_pretrained_tokenizer_tensorflow_tokenizers | 
+| 0 | tokenizer - tokenizers - tokenization - tokenize - token | 2407 | 0_tokenizer_tokenizers_tokenization_tokenize | 
+| 1 | cuda - memory - tensorflow - pytorch - gpu | 1379 | 1_cuda_memory_tensorflow_pytorch | 
+| 2 | longformer - longformers - longformertokenizerfast - longformerformultiplechoice - tf | 791 | 2_longformer_longformers_longformertokenizerfast_longformerformultiplechoice | 
+| 3 | modelcard - modelcards - card - model - cards | 510 | 3_modelcard_modelcards_card_model | 
+| 4 | summarization - summaries - summary - sentences - text | 431 | 4_summarization_summaries_summary_sentences | 
+| 5 | s2s - seq2seq - runseq2seq - eval - examplesseq2seq | 405 | 5_s2s_seq2seq_runseq2seq_eval | 
+| 6 | squaddataset - attributeerror - squadpy - valueerror - modulenotfounderror | 381 | 6_squaddataset_attributeerror_squadpy_valueerror | 
+| 7 | typos - typo - doc - docstring - fix | 324 | 7_typos_typo_doc_docstring | 
+| 8 | readmemd - readmetxt - readme - modelcard - file | 299 | 8_readmemd_readmetxt_readme_modelcard | 
+| 9 | gpt2 - gpt2xl - gpt - gpt2tokenizer - gpt3 | 261 | 9_gpt2_gpt2xl_gpt_gpt2tokenizer | 
+| 10 | rag - ragtokenforgeneration - ragsequenceforgeneration - tokenizer - gluepy | 256 | 10_rag_ragtokenforgeneration_ragsequenceforgeneration_tokenizer | 
+| 11 | transformerscli - importerror - transformers - transformer - transformerxl | 232 | 11_transformerscli_importerror_transformers_transformer | 
+| 12 | ner - pipeline - pipelines - pipelinespy - nerpipeline | 196 | 12_ner_pipeline_pipelines_pipelinespy | 
+| 13 | testing - tests - test - installationtest - speedup | 189 | 13_testing_tests_test_installationtest | 
+| 14 | checkpoint - trainertrain - checkpoints - checkpointing - trainersavecheckpoint | 162 | 14_checkpoint_trainertrain_checkpoints_checkpointing | 
+| 15 | flax - flaxelectraformaskedlm - flaxelectraforpretraining - flaxjax - flaxelectramodel | 119 | 15_flax_flaxelectraformaskedlm_flaxelectraforpretraining_flaxjax | 
+| 16 | generationbeamsearchpy - generatebeamsearch - beamsearch - nonbeamsearch - beam | 109 | 16_generationbeamsearchpy_generatebeamsearch_beamsearch_nonbeamsearch | 
+| 17 | onnxonnxruntime - onnx - onnxexport - 04onnxexport - 04onnxexportipynb | 99 | 17_onnxonnxruntime_onnx_onnxexport_04onnxexport | 
+| 18 | labelsmoothednllloss - labelsmoothingfactor - label - labels - labelsmoothing | 86 | 18_labelsmoothednllloss_labelsmoothingfactor_label_labels | 
+| 19 | cachedir - cache - cachedpath - cached - caching | 77 | 19_cachedir_cache_cachedpath_cached | 
+| 20 | wav2vec2 - wav2vec - wav2vec20 - wav2vec2forctc - wav2vec2xlrswav2vec2 | 61 | 20_wav2vec2_wav2vec_wav2vec20_wav2vec2forctc | 
+| 21 | notebook - notebooks - community - colab - t5 | 55 | 21_notebook_notebooks_community_colab | 
+| 22 | wandbproject - wandb - wandbcallback - wandbdisabled - wandbdisabledtrue | 39 | 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 | isort - blackisortflake8 - dependencies - github - matplotlib | 18 | 25_isort_blackisortflake8_dependencies_github | 
+| 26 | pplm - pr - deprecated - variable - ppl | 16 | 26_pplm_pr_deprecated_variable | 
+| 27 | ga - fork - forks - forked - push | 14 | 27_ga_fork_forks_forked | 
+| 28 | indexerror - runtimeerror - index - indices - missingindex | 11 | 28_indexerror_runtimeerror_index_indices |
+  
+</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: 1.23.5
+* HDBSCAN: 0.8.33
+* UMAP: 0.5.4
+* Pandas: 1.5.3
+* Scikit-Learn: 1.2.2
+* Sentence-transformers: 2.2.2
+* Transformers: 4.34.0
+* Numba: 0.56.4
+* Plotly: 5.15.0
+* Python: 3.10.12

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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+oid sha256:23df0a00318978d47672bbdb8b6a196b4df9c8270505ecc0e04f13d48029c4c7
+size 46168