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("flumboyantApple/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 | bert - pytorch - tensorflow - pretrained - gpu | 12 | -1_bert_pytorch_tensorflow_pretrained | 
+| 0 | tokenizer - tokenizers - tokenization - tokenize - encoderdecoder | 2279 | 0_tokenizer_tokenizers_tokenization_tokenize | 
+| 1 | cuda - pytorch - tensorflow - gpu - gpus | 1830 | 1_cuda_pytorch_tensorflow_gpu | 
+| 2 | modelcard - modelcards - card - model - cards | 887 | 2_modelcard_modelcards_card_model | 
+| 3 | seq2seq - s2s - seq2seqtrainer - seq2seqdataset - runseq2seq | 451 | 3_seq2seq_s2s_seq2seqtrainer_seq2seqdataset | 
+| 4 | trainer - trainertrain - trainers - training - evaluateduringtraining | 445 | 4_trainer_trainertrain_trainers_training | 
+| 5 | albertbasev2 - albertforpretraining - albert - albertformaskedlm - albertmodel | 435 | 5_albertbasev2_albertforpretraining_albert_albertformaskedlm | 
+| 6 | gpt2 - gpt2tokenizer - gpt2xl - gpt2tokenizerfast - gpt | 347 | 6_gpt2_gpt2tokenizer_gpt2xl_gpt2tokenizerfast | 
+| 7 | typos - typo - fix - correction - fixed | 278 | 7_typos_typo_fix_correction | 
+| 8 | readmemd - readmetxt - readme - file - camembertbasereadmemd | 274 | 8_readmemd_readmetxt_readme_file | 
+| 9 | t5 - t5model - tf - t5base - t5large | 259 | 9_t5_t5model_tf_t5base | 
+| 10 | transformerscli - transformers - transformer - importerror - import | 228 | 10_transformerscli_transformers_transformer_importerror | 
+| 11 | ci - testing - tests - testgeneratefp16 - test | 198 | 11_ci_testing_tests_testgeneratefp16 | 
+| 12 | longformerforquestionanswering - questionansweringpipeline - tfalbertforquestionanswering - distilbertforquestionanswering - questionanswering | 142 | 12_longformerforquestionanswering_questionansweringpipeline_tfalbertforquestionanswering_distilbertforquestionanswering | 
+| 13 | pipeline - pipelines - ner - fixpipeline - nerpipeline | 140 | 13_pipeline_pipelines_ner_fixpipeline | 
+| 14 | longformer - longformers - longform - longformerlayer - longformermodel | 136 | 14_longformer_longformers_longform_longformerlayer | 
+| 15 | benchmark - benchmarks - accuracy - precision - hardcoded | 113 | 15_benchmark_benchmarks_accuracy_precision | 
+| 16 | onnx - onnxexport - onnxonnxruntime - onnxruntime - 04onnxexport | 77 | 16_onnx_onnxexport_onnxonnxruntime_onnxruntime | 
+| 17 | generationbeamsearchpy - generatebeamsearch - beamsearch - nonbeamsearch - beam | 76 | 17_generationbeamsearchpy_generatebeamsearch_beamsearch_nonbeamsearch | 
+| 18 | flax - flaxelectraformaskedlm - flaxelectraforpretraining - flaxjax - flaxelectramodel | 75 | 18_flax_flaxelectraformaskedlm_flaxelectraforpretraining_flaxjax | 
+| 19 | datacollatorforlanguagemodelingfile - datacollatorforlanguagemodeling - datacollatorforlanguagemodelling - datacollatorforpermutationlanguagemodeling - runlanguagemodelingpy | 49 | 19_datacollatorforlanguagemodelingfile_datacollatorforlanguagemodeling_datacollatorforlanguagemodelling_datacollatorforpermutationlanguagemodeling | 
+| 20 | huggingfacetokenizers297 - huggingfacetransformers - huggingface - huggingfaces - huggingfacecn | 43 | 20_huggingfacetokenizers297_huggingfacetransformers_huggingface_huggingfaces | 
+| 21 | cachedir - cache - cachedpath - caching - cached | 43 | 21_cachedir_cache_cachedpath_caching | 
+| 22 | notebook - notebooks - blenderbot3b - community - blenderbot | 35 | 22_notebook_notebooks_blenderbot3b_community | 
+| 23 | wandbproject - ga - wandbcallback - wandb - fork | 33 | 23_wandbproject_ga_wandbcallback_wandb | 
+| 24 | closed - adding - add - bort - added | 32 | 24_closed_adding_add_bort | 
+| 25 | electra - electrapretrainedmodel - electraformaskedlm - electralarge - electraformultiplechoice | 27 | 25_electra_electrapretrainedmodel_electraformaskedlm_electralarge | 
+| 26 | layoutlm - layout - layoutlmtokenizer - layoutlmbaseuncased - tf | 23 | 26_layoutlm_layout_layoutlmtokenizer_layoutlmbaseuncased | 
+| 27 | pplm - pr - deprecated - variable - ppl | 18 | 27_pplm_pr_deprecated_variable | 
+| 28 | isort - blackisortflake8 - github - repo - version | 15 | 28_isort_blackisortflake8_github_repo |
+  
+</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: 1.23.3
+* HDBSCAN: 0.8.38.post1
+* UMAP: 0.5.6
+* Pandas: 1.5.3
+* Scikit-Learn: 1.1.2
+* Sentence-transformers: 3.0.1
+* Transformers: 4.44.1
+* Numba: 0.60.0
+* Plotly: 5.10.0
+* Python: 3.9.18

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,
+  "zeroshot_min_similarity": 0.7,
+  "zeroshot_topic_list": null,
+  "embedding_model": "sentence-transformers/all-MiniLM-L6-v2"
+}

topic_embeddings.safetensors

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+oid sha256:4d3925508fa947a70d4c96537cc1e9c19051a3a42981ddb76f142590182117fb
+size 46168