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--- |
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language: |
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- en |
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- zh |
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- de |
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- es |
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- ru |
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- ko |
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- fr |
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- ja |
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- pt |
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- tr |
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- pl |
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- ca |
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- nl |
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- ar |
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- sv |
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- it |
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- id |
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- hi |
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- fi |
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- vi |
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- he |
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- uk |
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- el |
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- ms |
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- cs |
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- ro |
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- da |
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- hu |
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- ta |
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- 'no' |
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- th |
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- ur |
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- hr |
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- bg |
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- lt |
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- la |
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- mi |
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- ml |
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- cy |
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- sk |
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- te |
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- fa |
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- lv |
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- bn |
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- sr |
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- az |
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- sl |
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- kn |
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- et |
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- mk |
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- br |
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- eu |
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- is |
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- hy |
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- ne |
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- mn |
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- bs |
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- kk |
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- sq |
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- sw |
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- gl |
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- mr |
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- pa |
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- si |
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- km |
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- sn |
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- yo |
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- so |
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- af |
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- oc |
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- ka |
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- be |
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- tg |
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- sd |
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- gu |
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- am |
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- yi |
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- lo |
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- uz |
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- fo |
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- ht |
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- ps |
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- tk |
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- nn |
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- mt |
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- sa |
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- lb |
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- my |
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- bo |
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- tl |
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- mg |
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- as |
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- tt |
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- haw |
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- ln |
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- ha |
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- ba |
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- jw |
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- su |
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- yue |
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tags: |
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- audio |
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- automatic-speech-recognition |
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- int8 |
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- quanto |
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- faster-whisper |
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license: apache-2.0 |
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library_name: ctranslate2 |
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--- |
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# Model Card for Model ID |
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This model is quantized using the [Quanto Python Package](https://github.com/huggingface/quanto) and the [CTranslate2 Python Package](https://github.com/OpenNMT/CTranslate2). |
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From my early tests: |
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- Much less GPU memory required |
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- It seems that performance is on par with the original |
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- It seems that this combination is faster than just using the CTranslate2 int8 quantization. |
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Quantization method TBA. |
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To use this model, use the faster_whisper module as stated in [the original faster-whisper model](https://huggingface.co/Systran/faster-whisper-large-v3). |
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Or use [WhisperX](https://github.com/m-bain/whisperX), this is what I used for my small tests (do not forget to set dtype to int8). |
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Any benchmark results are appreciated. I probably do not have time to do it myself. |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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- **Developed by:** [More Information Needed] |
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- **Funded by [optional]:** [More Information Needed] |
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- **Shared by [optional]:** [More Information Needed] |
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- **Model type:** [More Information Needed] |
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- **Language(s) (NLP):** [More Information Needed] |
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- **License:** [More Information Needed] |
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- **Finetuned from model [optional]:** [More Information Needed] |
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### Model Sources [optional] |
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- **Repository:** [More Information Needed] |
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- **Paper [optional]:** [More Information Needed] |
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- **Demo [optional]:** [More Information Needed] |
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## Uses |
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### Direct Use |
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> |
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[More Information Needed] |
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### Downstream Use [optional] |
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[More Information Needed] |
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### Out-of-Scope Use |
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[More Information Needed] |
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## Bias, Risks, and Limitations |
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<!-- This section is meant to convey both technical and sociotechnical limitations. --> |
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[More Information Needed] |
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### Recommendations |
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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[More Information Needed] |
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## Training Details |
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### Training Data |
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> |
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[More Information Needed] |
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### Training Procedure |
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> |
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#### Preprocessing [optional] |
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[More Information Needed] |
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#### Training Hyperparameters |
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> |
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#### Speeds, Sizes, Times [optional] |
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> |
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[More Information Needed] |
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## Evaluation |
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<!-- This section describes the evaluation protocols and provides the results. --> |
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### Testing Data, Factors & Metrics |
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#### Testing Data |
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<!-- This should link to a Dataset Card if possible. --> |
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[More Information Needed] |
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#### Factors |
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> |
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[More Information Needed] |
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#### Metrics |
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<!-- These are the evaluation metrics being used, ideally with a description of why. --> |
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[More Information Needed] |
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### Results |
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[More Information Needed] |
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#### Summary |
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## Model Examination [optional] |
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<!-- Relevant interpretability work for the model goes here --> |
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[More Information Needed] |
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## Environmental Impact |
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> |
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). |
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- **Hardware Type:** [More Information Needed] |
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- **Hours used:** [More Information Needed] |
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- **Cloud Provider:** [More Information Needed] |
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- **Compute Region:** [More Information Needed] |
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- **Carbon Emitted:** [More Information Needed] |
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## Technical Specifications [optional] |
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### Model Architecture and Objective |
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[More Information Needed] |
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### Compute Infrastructure |
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[More Information Needed] |
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#### Hardware |
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[More Information Needed] |
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#### Software |
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[More Information Needed] |
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## Citation [optional] |
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> |
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**BibTeX:** |
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[More Information Needed] |
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**APA:** |
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[More Information Needed] |
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## Glossary [optional] |
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> |
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[More Information Needed] |
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## More Information [optional] |
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[More Information Needed] |
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## Model Card Authors [optional] |
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[More Information Needed] |
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## Model Card Contact |
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