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("sweetapplee/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 - tokenizer - tokenizers - pretrained - pytorch | 16 | -1_bert_tokenizer_tokenizers_pretrained | 
+| 0 | tokenization - tokenizer - tokenizers - token - tokens | 2184 | 0_tokenization_tokenizer_tokenizers_token | 
+| 1 | tf - tpu - t5 - tftrainer - onnx | 1761 | 1_tf_tpu_t5_tftrainer | 
+| 2 | modelcard - modelcards - card - model - cards | 939 | 2_modelcard_modelcards_card_model | 
+| 3 | importerror - attributeerror - valueerror - typeerror - runmlmpy | 486 | 3_importerror_attributeerror_valueerror_typeerror | 
+| 4 | doc - docstring - docstrings - docs - document | 449 | 4_doc_docstring_docstrings_docs | 
+| 5 | albertforpretraining - xlnet - albertbasev2 - albertformaskedlm - xlnetlmheadmodel | 400 | 5_albertforpretraining_xlnet_albertbasev2_albertformaskedlm | 
+| 6 | gpt2 - gpt2tokenizer - gpt2xl - gpt - gpt2tokenizerfast | 348 | 6_gpt2_gpt2tokenizer_gpt2xl_gpt | 
+| 7 | readmemd - readmetxt - readme - file - camembertbasereadmemd | 273 | 7_readmemd_readmetxt_readme_file | 
+| 8 | s2s - s2sdistill - s2t - s2strainer - exampless2s | 260 | 8_s2s_s2sdistill_s2t_s2strainer | 
+| 9 | longformer - longformers - longformerformultiplechoice - longformertokenizerfast - globalattentionmask | 216 | 9_longformer_longformers_longformerformultiplechoice_longformertokenizerfast | 
+| 10 | transformerscli - transformers - transformer - importerror - transformerxl | 194 | 10_transformerscli_transformers_transformer_importerror | 
+| 11 | tests - testing - slow - test - faster | 187 | 11_tests_testing_slow_test | 
+| 12 | cuda - cuda0 - memory - ram - gpus | 159 | 12_cuda_cuda0_memory_ram | 
+| 13 | pipeline - pipelines - ner - nerpipeline - featureextractionpipeline | 145 | 13_pipeline_pipelines_ner_nerpipeline | 
+| 14 | questionansweringpipeline - longformerforquestionanswering - answering - questionanswering - distilbertforquestionanswering | 144 | 14_questionansweringpipeline_longformerforquestionanswering_answering_questionanswering | 
+| 15 | trainertrain - trainer - loggingstrategy - logging - training | 139 | 15_trainertrain_trainer_loggingstrategy_logging | 
+| 16 | benchmark - benchmarks - accuracy - precision - comparison | 139 | 16_benchmark_benchmarks_accuracy_precision | 
+| 17 | labelsmoothednllloss - label - labelsmoothingfactor - labels - labelsmoothing | 75 | 17_labelsmoothednllloss_label_labelsmoothingfactor_labels | 
+| 18 | huggingfacemaster - huggingfacetokenizers297 - huggingface - huggingfaces - huggingfacetransformers | 74 | 18_huggingfacemaster_huggingfacetokenizers297_huggingface_huggingfaces | 
+| 19 | generationbeamsearchpy - generatebeamsearch - beamsearch - nonbeamsearch - beam | 73 | 19_generationbeamsearchpy_generatebeamsearch_beamsearch_nonbeamsearch | 
+| 20 | wav2vec2 - wav2vec - wav2vec20 - wav2vec2forctc - wav2vec2xlrswav2vec2 | 59 | 20_wav2vec2_wav2vec_wav2vec20_wav2vec2forctc | 
+| 21 | flax - flaxelectraformaskedlm - flaxelectraforpretraining - flaxjax - flaxelectramodel | 52 | 21_flax_flaxelectraformaskedlm_flaxelectraforpretraining_flaxjax | 
+| 22 | notebook - notebooks - notebookprogresscallback - community - colab | 51 | 22_notebook_notebooks_notebookprogresscallback_community | 
+| 23 | wandbproject - wandb - wandbcallback - wandbdisabled - wandbdisabledtrue | 40 | 23_wandbproject_wandb_wandbcallback_wandbdisabled | 
+| 24 | cachedir - cache - cachedpath - caching - cached | 34 | 24_cachedir_cache_cachedpath_caching | 
+| 25 | closed - add - bort - added - deleted | 33 | 25_closed_add_bort_added | 
+| 26 | electra - electrapretrainedmodel - electraformaskedlm - electralarge - electraformultiplechoice | 26 | 26_electra_electrapretrainedmodel_electraformaskedlm_electralarge | 
+| 27 | layoutlm - layout - layoutlmtokenizer - layoutlmbaseuncased - tf | 26 | 27_layoutlm_layout_layoutlmtokenizer_layoutlmbaseuncased | 
+| 28 | isort - blackisortflake8 - github - repo - version | 18 | 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
+
+## 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: 4.34.1
+* 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 sha256:23c2d5624e4004135bc87b2b08d7e7c7b6d82b2b57c02817717ac60f1f8c26f9
+size 46168