README.md

---
tags:
- bertopic
library_name: bertopic
pipeline_tag: text-classification
---

# hub_issues_topocs

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/hub_issues_topocs")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 156
* Number of training documents: 6427

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| -1 | model - version - training - add - base | 10 | Outlier Topic | 
| 0 | yes - upscaling - embeddings - dir - 18 | 1785 | Yes Upscaling VAE Embeddings | 
| 1 | images - image - img2img - generated - black | 218 | Image Distortion Investigation | 
| 2 | languages - language - chinese - support - multilingual | 169 | Multilingual Language Support | 
| 3 | request - thesis - checker - request request - work | 103 | DOI request and thesis checker | 
| 4 | bloom - 176b - bloomz - bert - 7b1 | 95 | Bloom inference on BERT | 
| 5 | api - inference api - hosted - inference - hosted inference | 80 | Configuring Inference API | 
| 6 | report report - report - reports - look - awesome | 78 | Awesome Reports | 
| 7 | use model - run model - model run - model use - tune model | 73 | Use model instructions | 
| 8 | request access - access request - access - request - request requesting | 65 | Access Request Solution | 
| 9 | colab - google - google colab - model google - collab | 64 | "Running Galactica on Colab" | 
| 10 | json - config json - config - json file - file named | 62 | JSON configuration files | 
| 11 | load model - load - model working - unable load - unable | 60 | "Model loading issues" | 
| 12 | text - text generation - words - truncated - generation | 57 | Text Generation Techniques | 
| 13 | label - labels - tags - classifier - entity | 57 | Document Labels | 
| 14 | data - model dataset - dataset - train model - used train | 55 | Model Training Data | 
| 15 | issue report - issue - report - 论文 - artists | 55 | Ethical Issues in Artists' Legal Discussion | 
| 16 | loading - loading model - error loading - model error - load model | 55 | Model Loading Errors | 
| 17 | error error - error - 500 error - connection - unknown error | 49 | Error 500 Connection | 
| 18 | train model - train - trained - model did - model trained | 46 | Training models in Arabic | 
| 19 | stable diffusion - diffusion - stable - diffusion v1 - diffusion webui | 46 | Stable Diffusion Downloads | 
| 20 | question - answers - questions - tts - double | 45 | Question about Fig.2c | 
| 21 | length - max - maximum - limit - sequence length | 45 | Length Limits and Token Length | 
| 22 | model model - model architecture - generator - architecture - type | 42 | Model Architecture | 
| 23 | commercial - license - commercial use - license license - mit | 41 | Commercial Use License | 
| 24 | transformers - transformer - sentence transformers - sentence - using transformers | 40 | Issues with sentence transformers | 
| 25 | huggingface - hugging face - hugging - face - using hugging | 40 | Hugging Face model usage | 
| 26 | legal - legal issue - issue report - issue - report | 40 | Legal Issues Reports | 
| 27 | v2 - v3 - anime - wav2vec2 - virus | 40 | Anime Virus Detection Vae | 
| 28 | tutorials - thread - tricks - 26 - tips | 39 | Stable Diffusion 26+ Tutorials | 
| 29 | difference - fp16 - dpm - opus - opus mt | 39 | Difference between phase1 and phase2 | 
| 30 | tokenizer - using from_pretrained - loading - error loading - load | 37 | Tokenizer Loading Error | 
| 31 | output - extraction - truncated - summaries - outputs | 37 | Output Extraction | 
| 32 | attribute - object - attributeerror - typeerror - string | 36 | AttributeError in object attributes | 
| 33 | ckpt file - ckpt - file ckpt - file - ckpt files | 36 | CKPT file location | 
| 34 | dataset dataset - dataset - source dataset - datasets - source | 36 | dataset source semantic search | 
| 35 | size - mismatch - discrepancy - vocab size - dimensionality | 36 | Size Mismatch Discrepancy | 
| 36 | license - license license - permission - agreement - licence | 36 | License Agreement | 
| 37 | model card - card - card model - building model - building | 35 | Model Card Typos | 
| 38 | demo - space - spaces - gradio - cause | 35 | Troubleshooting Gradio Demo | 
| 39 | commercially - does model - commercial - model used - usable | 34 | Commercial Usability of AI Model | 
| 40 | automatic1111 - webui - automatic - ui - web ui | 33 | Automatic1111 WebUI | 
| 41 | import - transformers - module - failed - export | 33 | ImportError in Transformers Module | 
| 42 | example - examples - example use - prompt example - usage example | 33 | Example Usage | 
| 43 | audio - noise - spectrogram - second - speaker | 33 | Audio Transcription and Conversion | 
| 44 | cool - love - idea - amazing - great | 32 | "cool and amazing" | 
| 45 | language model - language - kenlm - lm - multilingual | 32 | Language Model Inference with KenLM | 
| 46 | really - nice - cool - love - amazing | 32 | amazing model | 
| 47 | sagemaker - endpoint - deployment - deploy - amazon | 32 | Deploying SageMaker Endpoints | 
| 48 | training training - training - training steps - general - video | 31 | "Training Steps Video" | 
| 49 | tokenizer - problems - masked - tokenizer tokenizer - tokens | 31 | Tokenizer Problems | 
| 50 | sd - sd2 - sd sd - does support - wd | 30 | Using SD with Different Versions | 
| 51 | test - testing - sampler - discussion - split | 30 | Testing Sampler Discussion | 
| 52 | argument - unexpected - keyword - typeerror - got | 30 | Unexpected keyword argument TypeError | 
| 53 | float - runtimeerror expected - runtimeerror - expected - type | 30 | RuntimeErrors with Float and Half Types | 
| 54 | dataset used - dataset - dataset dataset - used fine - used | 28 | Dataset Usage | 
| 55 | json - json file - model architecture - inconsistency - architecture | 28 | JSON file inconsistency | 
| 56 | usage - project - app - macos - usage questions | 28 | Usage with Sherpa | 
| 57 | reproduce - results - result - civitai - reproducing results | 28 | Reproduce Result Difficulty | 
| 58 | gene - cell - question generation - generation - geneformer | 27 | Gene Embedding Generation | 
| 59 | gpu - gpus - multiple - gpu run - model multiple | 27 | Multi-GPU Model Execution | 
| 60 | tokenizer use - wlop - mean - token - webui version | 26 | Tokenizer for Cantonese | 
| 61 | model fine - tuning model - fine tuning - fine - tuning | 26 | Fine-Tuning the Model | 
| 62 | model training - training model - training - redshift - model model | 26 | Model Training | 
| 63 | bot - discord - tesla - chat - character | 26 | Tesla Discord Bot 2021 | 
| 64 | work - doesn work - doesn - dont - does appear | 26 | Non-functional potty lora | 
| 65 | use use - use - best - way use - methods | 26 | Best ways to use | 
| 66 | report card - metadata - card - report -  | 26 | Metadata Report Card | 
| 67 | guide - instructions - guidance - prompt - cost | 25 | Fine-tuning guide instructions | 
| 68 | code - finetuning code - finetuning - fine tuning - tuning | 25 | Fine-tuning Code Sample | 
| 69 | dataset - custom dataset - dataset fine - custom - fine tuning | 25 | Custom dataset fine-tuning | 
| 70 | safetensors - safetensor - version - version safetensors - safetensor version | 25 | SafeTensors Version Inquiry | 
| 71 | model based - task model - model changes - bring - v7 | 25 | Model Description and Changes | 
| 72 | weights - weight - flax - diffusers weights - load weights | 25 | Outdated Flax Weights | 
| 73 | style - modern - mode - new - dark mode | 24 | Style in Modern Technology | 
| 74 | convert - format - trying convert - safetensors - converter | 24 | Safetensors conversion error | 
| 75 | checkpoint - save - checkpoint file - checkpoints - restore | 24 | Checkpoint Safety Restore | 
| 76 | t5 - flan t5 - flan - google flan - xxl | 23 | T5 vs Flan-T5 Differences | 
| 77 | download model - model load - download - load - model download | 23 | "Model Download" | 
| 78 | access access - access - access need - need access - need | 23 | Access Request Assistance | 
| 79 | model details - details model - details - information model - model access | 23 | Model Details | 
| 80 | job - excellent - nice - great - congrats | 23 | Job Well Done | 
| 81 | onnx - conversion - onnx conversion - convert - torchscript | 22 | ONNX Conversion Implementation | 
| 82 | git - repository - repo - cloning - slow | 22 | Git repository cloning issues | 
| 83 | online - 50 - 200 - buy - annotator | 22 | Buy Medications Online | 
| 84 | access - request access - acces request - access request - request | 22 | Access Request | 
| 85 | cuda - cuda memory - memory - cuda error - memory cuda | 22 | CUDA memory out of error | 
| 86 | api model - api - inference api - model api - trying use | 22 | API Model Errors | 
| 87 | training data - data training - data - training dataset - training | 22 | Data Training Examples | 
| 88 | pipeline - valid - pipe - sentence similarity - similarity | 21 | Pipeline error analysis | 
| 89 | tensor - tensors - device - expected - size | 21 | Tensor size mismatch errors | 
| 90 | in_silico_perturber - eos_token_id - switch - 64 - encoder | 21 | Error in decoder generation | 
| 91 | pytorch_model - pytorch_model bin - bin - diffusion_pytorch_model bin - diffusion_pytorch_model | 21 | Missing pytorch_model.bin file | 
| 92 | 404 - url - https - https huggingface - resolve | 21 | 404 error Huggingface documents | 
| 93 | requirements - acess - feature request - request request - feature | 21 | System Requirements Access | 
| 94 | info - technical - details - information - detailed | 21 | Technical Details Inquiry | 
| 95 | hello - hi - good - translates - 100 | 20 | Greetings and Translations | 
| 96 | accuracy - drop - compatibility - precision - half precision | 20 | Accuracy Drop in Precision | 
| 97 | access request - request access - access - request - new | 20 | Access Request | 
| 98 | file missing - log - filenotfounderror - location - sorry | 20 | File Not Found | 
| 99 | model card - card - link model - link - example model | 20 | Broken link in model | 
| 100 | python - kernel - 10 - pytorch - talks | 20 | Python usage and errors | 
| 101 | bug - fix - racist - possible bug - thing | 19 | Bug Fix with Racist Bug | 
| 102 | training code - code training - code - share - share training | 19 | "Training Code Sharing" | 
| 103 | license - accept - license license - model accept - indication | 19 | Model License | 
| 104 | gpt - protgpt2 - 6b - jt - gpt jt | 19 | GPT-JT-6B-v1 Abilities | 
| 105 | report report - report -  -  -  | 19 | Multiple Reports on Topic | 
| 106 | tuning fine - tune fine - fine - fine tuning - tuning | 18 | Fine-tuning for domain adaptation | 
| 107 | inpaint model - inpaint - ix - size model - model pruned | 18 | Inpaint Model | 
| 108 | config file - config - tokenizer config - files config - file | 18 | Config File Troubleshooting | 
| 109 | sample code - example - sample - copied - error example | 18 | Issues with sample code | 
| 110 | nsfw - nsfw content - content - disable - safety | 18 | NSFW Content Filtering | 
| 111 | length - summary - longformer - summary length - text length | 18 | Length of Summaries | 
| 112 | access download - access - download - access access - download working | 18 | Access Download | 
| 113 | thank - thanks - just want - pretty - request thank | 18 | Thank you efforts | 
| 114 | sd v1 - v1 - ema ckpt - sd - ema | 18 | Access to sd-v1-4-full-ema.ckpt | 
| 115 | padding_side - tokens - token - cls token - token id | 18 | Padding and token discrepancy | 
| 116 | amd - vram - gb - gpu - 448 | 17 | "AMD GPU compatibility" | 
| 117 | dataset - pretraining - dataset dataset - datasets - request dataset | 17 | Dataset Pretraining | 
| 118 | version - ggml version - version ggml - ggml - pytorch version | 17 | "Version Possibility" | 
| 119 | memory - leak - a100 - cuda memory - memory google | 17 | Memory-related Issues | 
| 120 | trigger - words - word - trigger word - semantic | 17 | Trigger words and semantic search | 
| 121 | result - results - output - score - ways | 16 | Visualizing Inference Results | 
| 122 | sd - tested - sd sd - lora training - ui | 16 | Stable Diffusion LORA Training | 
| 123 | ckpt file - bin - convert - weights - dreambooth | 16 | Convert Diffusion Diffusers to CKPT | 
| 124 | need help - help - help help - need - started | 16 | Need Help Getting Started | 
| 125 | keyerror - key - exception error - key error - codegen | 16 | KeyError Troubleshooting | 
| 126 | controlnet - control - a1111 - installed - model embedding | 16 | ControlNet not working | 
| 127 | implementation - issue - solved - np - experiencing | 16 | Implementation Issue Fix | 
| 128 | runtimeerror - time series - everytime - process runtimeerror - try run | 16 | Time Series Runtime Error | 
| 129 | use use - use - use readme - use diffusers - tk | 15 | How to use Diffusers | 
| 130 | training dataset - dataset used - used dataset - nli - used training | 15 | Training Dataset Used | 
| 131 | yaml files - colab pc - install run - diffusion google - train custom | 15 | Stable Diffusion Tutorials | 
| 132 | spam - deleted - removed - delete - contact | 15 | Removal of Spam Discussion | 
| 133 | details training - details - training - details details - details info | 14 | Training Details | 
| 134 | hyper parameters - hyper - parameters - provide - provide training | 14 | Hyperparameter Optimization | 
| 135 | fine tune - tune - ner - fine - emotions | 14 | Fine-tune Sentence Embeddings | 
| 136 | model using - using model - examples - question lora - models used | 14 | Inkpunk Diffusion model | 
| 137 | error running - running - running example - usage code - code | 14 | Error running example code | 
| 138 | difference - alpaca - model difference - original model - difference model | 14 | Model Differences | 
| 139 | install - locally - know install - run local - mini | 14 | "How to install locally" | 
| 140 | training script - script - script training - sharing training - midi | 13 | Training Script | 
| 141 | model file - missing model - corrupt - file model - file missing | 13 | Model File Issues | 
| 142 | error help - help error - help - solve - try | 13 | Error Help | 
| 143 | hardware - hardware requirements - requirements - gpu inference - requirements fine | 13 | Hardware Requirements for Inference | 
| 144 | update - updated - channel - expired - new update | 13 | update query status | 
| 145 | negative - negative prompt - negative prompts - prompts - prompt | 13 | "Negative Prompt Function" | 
| 146 | unable run - unable - run unable - run - human | 13 | Unable to run on local machine | 
| 147 | injection - nmkd gui - nmkd - tutorial videos - gui | 12 | Stable Diffusion Tutorial Videos | 
| 148 | download download - download - request acces - know download - fim | 12 | "Download Instructions" | 
| 149 | transformers - sentence transformers - huggingface transformers - different results - usage | 12 | Transformer Usage Discrepancy | 
| 150 | link - broken link - broken - documentation - expired | 11 | Broken links and documentation | 
| 151 | broke - padding - dead - kenlm - dropout | 11 | "Dead KenLM Finetuning" | 
| 152 | training question - question training - training process - question regarding - question | 11 | Training Process Question | 
| 153 | dataset training - training data - training dataset - data training - custom dataset | 11 | Training Data Quality | 
| 154 | download - download download - possible download - hd 18 - hd | 11 | Troubleshooting download errors |
  
</details>

## Training hyperparameters

* calculate_probabilities: False
* language: None
* low_memory: False
* min_topic_size: 10
* n_gram_range: (1, 1)
* nr_topics: None
* seed_topic_list: None
* top_n_words: 10
* verbose: True

## Framework versions

* Numpy: 1.22.4
* HDBSCAN: 0.8.33
* UMAP: 0.5.3
* Pandas: 1.5.3
* Scikit-Learn: 1.2.2
* Sentence-transformers: 2.2.2
* Transformers: 4.31.0
* Numba: 0.56.4
* Plotly: 5.13.1
* Python: 3.10.6