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README.md
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---
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license: apache-2.0
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---
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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-whsiper model](https://huggingface.co/Systran/faster-whisper-large-v3)
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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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<!-- Provide the basic links for the model. -->
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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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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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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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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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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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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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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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[More Information Needed]
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